1. Unit startpage
  2. Employees
  3. Dilip K. Prasad
Bilde av Prasad, Dilip K.
Bilde av Prasad, Dilip K.
Professor Department of Computer Science dilip.prasad@uit.no +4777645694 You can find me here

Dilip K. Prasad

Job description

Dilip K. Prasad (IEEE Senior Member) is a Professor at the Department of Computer Science, UiT The Arctic University of Norway. He received the Ph.D and B.Tech degree in Computer Science and Engineering from Nanyang Technological University, Singapore and Indian Institute of Technology (Indian School of Mines), Dhanbad, India, respectively. He was a senior research fellow at Nanyang Technological University, Singapore from 2015-2019 and research Fellow at the National University of Singapore from 2012-2015. Prior to Ph.D., he has worked for 5 years with IBM, Infosys, Mediatek and Philips. He has been selected as a Fellow for the Kauffman Global Scholarship in 2011, in which he was trained in entrepreneurship at Harvard University, MIT, Stanford University and the Kauffman Foundation. He has been awarded the Rolls-Royce Inventor Award in 2016. He has published 130+ internationally peer-reviewed research articles and patents. He is a co-founder of Bio-AI lab at UiT. Since 2019, he has secured ~21 million Euro research and innovation grant as a PI/co-PI from the European Union, Research Council of Norway. His research interest in sustainable AI, Scalable AI, Interpretable AI and application of AI for life sciences. He is a co-author of the book titled " Interpretability in Deep Learning ", Springer, 2023.

  • Himanshu Buckchash, Momojit Biswas, Rohit Agarwal, Dilip Kumar Prasad :
    Hedging Is Not All You Need: A Simple Baseline for Online Learning Under Haphazard Inputs
    arXiv 2024 DOI
  • Ronny Paul, Himanshu Buckchash, Shantipriya Parida, Dilip Kumar Prasad :
    Towards a More Inclusive AI: Progress and Perspectives in Large Language Model Training for the Sámi Language
    arXiv 2024 DOI
  • Hui Xue, Øyvind Haugseggen, Johan-Fredrik Røds, Bjørn-Morten Erdal Batalden, Dilip Kumar Prasad :
    Assessment of stress levels based on biosignal during the simulator-based maritime navigation training and its impact on sailing route reliability
    Transportation Research Interdisciplinary Perspectives (TRIP) 2024 ARKIV / DOI
  • Gauri Arora, Ankit Butola, Ruchi Rajput, Rohit Agarwal, Krishna Agarwal, Ludwig Alexander Horsch et al.:
    Taxonomy of hybridly polarized Stokes vortex beams
    Optics Express 2024 ARKIV / DOI
  • Momojit Biswas, Himanshu Buckchash, Dilip Kumar Prasad :
    pNNCLR: Stochastic pseudo neighborhoods for contrastive learning based unsupervised representation learning problems
    Neurocomputing 2024 ARKIV / DOI
  • Pragyan Banerjee, Shivam Milind Akarte, Prakhar Kumar, Muhammad Shamsuzzaman, Ankit Butola, Krishna Agarwal et al.:
    High-resolution imaging in acoustic microscopy using deep learning
    Machine Learning: Science and Technology 2024 ARKIV / DOI
  • Ayush Singh, Yash Bhambhu, Himanshu Buckchash, Deepak Kumar Gupta, Dilip Kumar Prasad :
    Latent Graph Attention for Spatial Context in Light-Weight Networks: Multi-Domain Applications in Visual Perception Tasks
    Applied Sciences 2024 DOI
  • Nirwan Banerjee, Samir Malakar, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    GUNet++: guided-U-Net-based compact image representation with an improved reconstruction mechanism
    Optical Society of America. Journal A: Optics, Image Science, and Vision (JOSA A) 2024 DOI
  • Ayush Somani, Ludwig Alexander Horsch, Ajit Bopardikar, Dilip Kumar Prasad :
    Propagating Transparency: A Deep Dive into the Interpretability of Neural Networks
    Nordic Machine Intelligence (NMI) 2024 FULLTEKST / ARKIV / DOI
  • Samir Malakar, Nirwan Banerjee, Dilip Kumar Prasad :
    Compact representation for memory-efficient storage of images using genetic algorithm-guided key pixel selection
    Engineering Applications of Artificial Intelligence 2024 ARKIV / DOI
  • Ayush Somani, Pragyan Banerjee, Manu Rastogi, Anowarul Habib, Krishna Agarwal, Dilip Kumar Prasad :
    Image Inpainting With Hypergraphs for Resolution Improvement in Scanning Acoustic Microscopy
    IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2023 ARKIV / FULLTEKST / DOI
  • Ayush Singh, Yash Bhambhu, Himanshu Buckchash, Deepak Gupta, Dilip Kumar Prasad :
    Latent Graph Attention for Enhanced Spatial Context
    arXiv.org 2023 DOI
  • Rohit Agarwal, Dilip Kumar Prasad, Ludwig Alexander Horsch, Deepak Kumar Gupta :
    Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts
    Transactions on Machine Learning Research (TMLR) 2023 ARKIV
  • Rohit Agarwal, Gyanendra Das, Saksham Aggarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Mabnet: Master Assistant Buddy Network With Hybrid Learning for Image Retrieval
    Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2023 ARKIV / DOI
  • Momojit Biswas, Himanshu Buckchash, Dilip Kumar Prasad :
    pNNCLR: Stochastic Pseudo Neighborhoods for Contrastive Learning based Unsupervised Representation Learning Problems
    arXiv.org 2023 DOI
  • Abhinanda Ranjit Punnakkal, Suyog Sakhahari Jadhav, Krishna Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    MiShape: 3D Shape Modelling of Mitochondria in Microscopy
    arXiv.org 2023 DOI
  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Modelling Irregularly Sampled Time Series Without Imputation
    arXiv.org 2023 DOI
  • Rohit Agarwal, Ankit Butola, Ludwig Alexander Horsch, Dilip Kumar Prasad, Krishna Agarwal :
    Taxonomy of hybridly polarized Stokes vortex beams
    arXiv.org 2023 DOI
  • Nirwan Banerjee, Samir Malakar, Deepak Kumar Gupta, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Guided U-Net Aided Efficient Image Data Storing with Shape Preservation
    Springer 2023 ARKIV / DOI
  • Pragyan Banerjee, Sibasish Mishra, Nitin Yadav, Krishna Agarwal, Frank Melandsø, Dilip Kumar Prasad et al.:
    Image inpainting in acoustic microscopy
    AIP Advances 2023 ARKIV / DOI
  • Abhinanda Ranjit Punnakkal, Gustav Godtliebsen, Ayush Somani, Sebastian Andres Acuna Maldonado, Åsa birna Birgisdottir, Dilip K. Prasad et al.:
    Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
    Journal of Visualized Experiments 2023 ARKIV / DOI
  • Sunil Bhatt, Ankit Butola, Anand Kumar, Pramila Thapa, Akshay Joshi, Suyog S. Jadhav et al.:
    Single-shot multispectral quantitative phase imaging of biological samples using deep learning
    Applied Optics 2023 ARKIV / DOI
  • Gustav Godtliebsen, Kenneth Bowitz Larsen, Zambarlal Babanrao Bhujabal, Ida Sundvor Opstad, Mireia Nager Grifo, Abhinanda Ranjit Punnakkal et al.:
    High-resolution visualization and assessment of basal and OXPHOS-induced mitophagy in H9c2 cardiomyoblasts
    Autophagy 2023 ARKIV / DOI
  • Zicheng Liu, Mayank Roy, Dilip K. Prasad, Krishna Agarwal :
    Physics-Guided Loss Functions Improve Deep Learning Performance in Inverse Scattering
    IEEE Transactions on Computational Imaging 2022 ARKIV / DOI
  • Chen Xie, Deepu Rajan, Dilip K. Prasad, Chai Quek :
    An embedded deep fuzzy association model for learning and explanation
    Applied Soft Computing 2022 DOI
  • Xinqiang Chen, Xingyu Wu, Dilip K. Prasad, Bing Wu, Octavian Postolache, Yongsheng Yang :
    Pixel-Wise Ship Identification From Maritime Images via a Semantic Segmentation Model
    IEEE Sensors Journal 2022 DOI
  • S Chattopadhyay, Antoni Malachowski, Jaya Kumari Swain, Roy Ambli Dalmo, Alexander Horsch, Dilip K. Prasad :
    Mapping Functional Changes in the Embryonic Heart of Atlantic Salmon Post Viral Infection Using AI Technique
    Proceedings of IEEE International Conference on Image Processing 2022 DOI
  • Ayush Somani, Arif Ahmed Sekh, Ida Sundvor Opstad, Åsa birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia et al.:
    Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning
    Biomedical Optics Express 2022 ARKIV / DOI
  • Sumit Rai, Arti Kumari, Dilip K. Prasad :
    Client Selection in Federated Learning under Imperfections in Environment
    AI 2022 ARKIV / DOI
  • Huixu Dong, Jiadong Zhou, Chen Qiu, Dilip K. Prasad, I-Ming Chen :
    Robotic Manipulations of Cylinders and Ellipsoids by Ellipse Detection With Domain Randomization
    IEEE/ASME transactions on mechatronics 2022 DOI
  • Divij Singh, Ayush Somani, Alexander Horsch, Dilip K. Prasad :
    Counterfactual Explainable Gastrointestinal and Colonoscopy Image Segmentation
    IEEE International Symposium on Biomedical Imaging 2022 ARKIV / DOI
  • Deepa Joshi, Ankit Butola, Sheetal Raosaheb Kanade, Dilip K. Prasad, Mithra Amitha Mithra, N.K. Singh et al.:
    Label-free non-invasive classification of rice seeds using optical coherence tomography assisted with deep neural network
    Optics and Laser Technology 2021 ARKIV / DOI
  • Soham Chattopadhyay, Laila Zary, Chai Quek, Dilip K. Prasad :
    Motivation detection using EEG signal analysis by residual-in-residual convolutional neural network
    Expert Systems With Applications 2021 ARKIV / DOI
  • S.W Jun, Arif Ahmed Sekh, Chai Quek, Dilip K. Prasad :
    seMLP: Self-evolving Multi-layer Perceptron in Stock Trading Decision Making
    SN Computer Science 2021 ARKIV / DOI
  • Ratnabali Pal, Arif Ahmed Sekh, Debi Prosad Dogra, Samarjit Kar, Partha Pratim Roy, Dilip K. Prasad :
    Topic-based Video Analysis: A Survey
    ACM Computing Surveys 2021 FULLTEKST / ARKIV / DOI
  • Q.E. Zhe, Arif Ahmed Sekh, Chai Quek, Dilip K. Prasad :
    Recurrent Self-evolving Takagi–Sugeno–Kan Fuzzy Neural Network (RST-FNN) based Type-2 Diabetic Modeling
    Springer 2021 DOI
  • Pranab Kanti Roy, Hiranmoy Mondal, Ashis Mallick, Dilip K. Prasad :
    Inverse and efficiency of heat transfer convex fin with multiple nonlinearities
    Heat Transfer 2021 ARKIV / DOI
  • Arif Ahmed Sekh, Ida Sundvor Opstad, Gustav Godtliebsen, Åsa Birna Birgisdottir, Balpreet Singh Ahluwalia, Krishna Agarwal et al.:
    Physics-based machine learning for subcellular segmentation in living cells
    Nature Machine Intelligence 2021 ARKIV / DOI
  • Jeow Li Huan, Arif Ahmed Sekh, Chai Quek, Dilip K. Prasad :
    Emotionally charged text classification with deep learning and sentiment semantic
    Neural Computing & Applications 2021 ARKIV / DOI
  • Hui Xue, Bjørn-Morten Batalden, Puneet Sharma, Jarle André Johansen, Dilip K. Prasad :
    Biosignal-Based Driving Skill Classification Using Machine Learning: A Case Study of Maritime Navigation
    Applied Sciences 2021 ARKIV / DOI
  • Ayush Somani, Arif Ahmed Sekh, Ida Sundvor Opstad, Åsa Birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia et al.:
    Digital Staining of Mitochondria in Label-free Live-cell Microscopy
    Springer 2021 DOI
  • Ayush Somani, Alexander Horsch, Dilip K. Prasad :
    Interpretability in Deep Learning
    Springer 2023 FULLTEKST
  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Code - Modelling Irregularly Sampled Time Series Without Imputation
    2023
  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Code - MABNET: Master Assistant Buddy Network for Image Retrieval
    2023
  • Rohit Agarwal, Krishna Agarwal, Alexander Horsch, Dilip K. Prasad :
    Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs
    2022 ARKIV
  • Huixu Dong, Jiadong Zhou, Chen Qiu, Dilip K. Prasad, I-Ming Chen :
    Learning-Based Ellipse Detection for Robotic Grasps of Cylinders and Ellipsoids
    2022
  • Xinqiang Chen, Xingyu Wu, Dilip K. Prasad, Bing Wu, Octavian Postolache, Yongsheng Yang :
    Corrections: Pixel-wise ship identification from maritime images via a semantic segmentation model (IEEE Sensors Journal (2022) 22:18 (18180-18191) DOI: 10.1109/JSEN.2022.3195959)
    IEEE Sensors Journal 2022 DOI
  • Dilip K. Prasad :
    Performing physics-based AI for ground truth hard sub-cellular organelle segmentation using simulated expert
    2021
  • Divij Singh, Ayush Somani, Alexander Horsch, Dilip K. Prasad :
    Performance improvement in deep learning models for outdoor semantic segmentation for autonomous driving for unstructured environment
    2021
  • Dilip K. Prasad :
    Physics based AI - 101
    2021

    • The 50 latest publications is shown on this page. See all publications in Cristin here →

    Publications outside Cristin

    Publications: 


    [Book] A. Somani, A. Horsch,  D.K. Prasad. "Interpretability in Deep Learning." Springer, pages 483, 2023. (Amazon)(Springer)

    Year 2024

    [J77]  P. Banerjee, S. M. Akarte, P. Kumar, M. Shamsuzzaman, A. Butola, K. Agarwal, D. K. Prasad, F. Melandsø, and A. Habib. "High-resolution imaging in acoustic microscopy using deep learning." Machine Learning: Science and Technology 5, no. 1, id: 015007, 2024

    [J76] G. Arora, A. Butola, R. Rajput, R. Agarwal, K. Agarwal, A. Horsch, D. K. Prasad, and Paramasivam Senthilkumaran. "Taxonomy of hybridly polarized Stokes vortex beams." Optics Express, 32, no. 5, pp. 7404-7416, 2024.

    [J75] X. Hui, H. Øyvind, J.-Fredrik Røds, B.-M. Batalden, and D. K. Prasad. "Assessment of stress levels based on biosignal during the simulator-based maritime navigation training and its impact on sailing route reliability." Transportation Research Interdisciplinary Perspectives 24 , id: 101047, 2024.

    [C51] U. Bamba, N. Anand, S.  Aggarwal, D.K. Prasad,  and D.K. Gupta, "Partial Binarization of Neural Networks for Budget-Aware Efficient Learning" In IEEE/CVF Winter Conference on Applications of Computer Vision, (pp. 2336-2345), 2024.

    Year 2023

    [J74] A.R. Punnakkal, G. Godtliebsen, A. Somani, S.A. Maldonado,  A.B. Birgisdottir,  D.K. Prasad, A. Horsch, K. Agarwal, "Analyzing Mitochondrial Morphology Through Simulation Supervised Learning." JoVE (Journal of Visualized Experiments), Mar 3(193):e64880, 2023. 

    [J73] R. Agarwal, D. Gupta, A. Horsch, D.K. Prasad, "Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts." Transactions on Machine Learning Research, 2023. 

    [C50] R. Tiwari, A. Chavan, D. Gupta, G. Mago, A. Gupta, A. Gupta, S.Sharan et al. "RCV2023 Challenges: Benchmarking Model Training and Inference for Resource-Constrained Deep Learning." In IEEE/CVF International Conference on Computer Vision, pp. 1534-1543. 2023.

    [C49] D. Gupta, G. Mago, A. Chavan, D. K. Prasad. "Patch gradient descent: Training neural networks on very large images." NeurIPS Workshop,2023.

    [J72] G. Godtliebsen, K.B. Larsen, Z. Bhujabal, I.S. Opstad, M. Nager, A.R. Punnakkal, T.B. Kalstad, R. Olsen, T. Lund, D.K. Prasad, K. Agarwal, A.B. Birgisdottir, "High-resolution visualization and assessment of basal and OXPHOS-induced mitophagy in H9c2 cardiomyoblasts." Autophagy,  Jul 7:1-20, 2023. 

    [C48] A. Somani, P. Banerjee, D. K. Gupta, A. Horsch, D.K. Prasad,  "Guided U-Net aided Efficient Image Data Storing with Shape Preservation." Asian Conference on Pattern Recognition (ACPR2023),  , Kitakyushu, Japan, 5-8 November 2023.

    [C47] N. Banerjee, S. Malakar, M. Rastogi, K. Agarwal, D.K. Prasad, A. Habib, "Image Inpainting With Hypergraphs for Resolution Improvement in Scanning Acoustic Microscopy." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops,  pp. 3112-3121, 2023.  

    [C46] S. Aggarwal, T. Gupta, P.K. Sahu, A. Chavan, R. Tiwari, D.K. Prasad, D. Gupta. "On designing light-weight object trackers through network pruning: Use CNNs or transformers?." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. 

    [C45] R. Agarwal, G. Das, S. Aggarwal, A. Horsch, D.K. Prasad, "MABNET: Master Assistant Buddy Network With Hybrid Learning for Image Retrieval." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. 

    [J71] P. Banerjee, S. Mishra, N. Yadav, K. Agarwal, F. Melandsø, D.K. Prasad, A. Habib, "Image inpainting in acoustic microscopy." AIP Advances, vol. 13, issue 4, 2023. 

    [J70] S. Bhatt, A. Butola, A. Kumar, P. Thapa, A. Joshi, S. Jadhav, N. Singh, D.K. Prasad, K. Agarwal, D.S. Mehta,  "Single-shot multispectral quantitative phase imaging of biological samples using deep learning." Applied Optics, vol. 62, issue 15, pp. 3989-99, 2023. 

    [J69] S. Jadhav, R. Kuchibhotla, K. Agarwal,  A. Habib,  D.K. Prasad. "Deep learning-based denoising of acoustic images generated with point contact method."  Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems,  Vol. 6, Issue 3, 2023. 

    [J68] D. Huixu, J. Zhou, C. Qiu, D. K. Prasad, and I-Ming Chen. "Robotic Manipulations of Cylinders and Ellipsoids by Ellipse Detection With Domain Randomization." IEEE/ASME Transactions on Mechatronics, vol. 28, issue 1, 2023.

    Year 2022

    [J67] C. Xie, D. Rajan, D.K. Prasad, C. Quek, "An embedded deep fuzzy association model for learning and explanation." Applied Soft Computing, vol. 131, article id. 109738, 2022. 

    [J66] A. Somani, A. A. Sekh, I.-S. Opstad, A. B. Birgisdottir, T. Myrmel, B. S. Ahluwalia, A. Horsch, K. Agarwal, D. K. Prasad. "Virtual Labeling of Mitochondria in Living Cells using Correlative Imaging and Physics-guided Deep Learning." Biomedical Optics Express, vol. 13, issue 10, pp. 5495-5516, 2022. 

    [C44] R. Agarwal, K. Agarwal, A. Horsch, D.K. Prasad. "Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs.", International Conference on Neural Information Processing (ICONIP), 2022.

    [J65] X. Chen, X. Xingyu, D. K. Prasad, B. Wu, O. Postolache, and Y. Yang. "Pixel-wise Ship Identification from Maritime Images via a Semantic Segmentation Model." IEEE Sensors Journal, vol. 22, issue 18, pp. 18180-18191, 2022.

    [J64] Z. Liu, M. Roy, D. K Prasad, K. Agarwal, “Physics-guided Loss Functions Improve Deep Learning Performance in Inverse Scattering,” IEEE Transactions on Computational Imaging, vol. 8, pp. 236-245, 2022.

    [C43] S Chattopadhyay, A Malachowski, JK Swain, RA Dalmo, A Horsch, D. K. Prasad, "Mapping functional changes in the embryonic heart of Atlantic salmon post viral infection using AI technique", International Conference on Image Processing (ICIP), Bordeux, France, 16-19 October, 2022.

    [C42] D. Singh, A. Somani, A. Horsch, D. K. Prasad, "Counterfactual Explainable Gastrointestinal and Colonoscopy Image Segmentation", International Symposium on Biomedical Imaging (ISBI), Kolkata, India, 28-31 March, 2022.

    [C41] H. Dong, J. Zhou, C. Qiu, D.K Prasad, I.-M. Chen, "Learning-Based Ellipse Detection for Robotic Grasps of Cylinders and Ellipsoids", IEEE International Conference on Robotics and Automation (ICRA), Phil, USA, 23-27 May 2022.

    [J63] S. Rai, A. Kumari, D. K. Prasad, “Client Selection in Federated Learning under Imperfections in Environment” AI, 2022.

    [J62]J. L. Huan, A. A. Sekh,  C. Quek, and D. K. Prasad, “Emotionally Charged Text Classification with Deep Learning and Sentiment Semantic,” Neural Computing and Applications, 34 (3), pp. 2341-2351, 2022.

    Year 2021

    [J61] A.A. Sekh, I-S. Opstad, G. Godtliebsen, A.B. Birgisdottir,  B.S. Ahluwalia, K. Agarwal, and D. K. Prasad, “Physics based machine learning for sub-cellular segmentation in living cells,” Nature Machine Intelligence, vol. 3, pp. 1071–1080, 2021. (PDF)(Source code)

    [J60] S. Chattopadhyay, L. Zary, C. Quek, D. K. Prasad, "Motivation detection using EEG signal analysis by residual-in-residual convolutional neural network",  Expert Systems With Applications, vol. 184, article id. 115548, 2021. (Codeocean reproducible code link)(Github Project page)(PDF)

    [J59] R. Pal, A. A. Sekh, D. P. Dogra, S. Kar, P. P. Roy, D. K. Prasad, "Topic-based Video Analysis: A Survey", ACM Computing Survey (CSUR), vol. 54, issue 6, pp. 1-34, 2021.

    [J58] S. W. Jun, A. A. Sekh, C. Quek, D. K. Prasad, "seMLP: Self-Evolving Multi-Layer Perceptron in Stock Trading Decision Making", SN Computer Science, vol. 2, issue 2, pp. 1-11, 2021. (Source code)

    [J57] D. Joshi, A. Butola, S. R. Kanade, D. K. Prasad, S.V. A. Mithra, N. K. Singh, D. S. Bisht, D. S. Mehta, "Label-free non-invasive classification of rice seeds using optical coherence tomography assisted with deep neural network", Optics and Laser Technology, vol. 137, 2021.(PDF)

    [J56] S. Jadhav, S. Acuña, I-S. Opstad, B. S. Ahluwalia, K. Agarwal, D. K. Prasad, "Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning", Biomedical Optics Express, vol. 12, issue 1, pp. 191-210, 2021. 

    [C40] D. Singh, A. Somani, A. Horsch, D. K. Prasad, "Performance improvement in deep learning models for outdoor semantic segmentation for autonomous driving for unstructured environment", Nordic AI Meet, Oslo, Norway, 1-2 Nov 2021. (2 Page abstract and oral presentation)

    [C39] A. Somani, A. A. Sekh, I.-S. Opstad, A. B. Birgisdottir, T. Myrmel, B. S. Ahluwalia, K. Agarwal, D. K. Prasad, A. Horsch, "Digital Staining of Mitochondria in Label-Free Live-Cell Microscopy", BVM Workshop 2021, Munich, Germany, 7-9 March 2021.

    [C38] Q. E. Zhe, A. A. Sekh, C. Quek, D. K. Prasad, "Recurrent Self-evolving Takagi–Sugeno–Kan Fuzzy Neural Network (RST-FNN) based Type-2 Diabetic Modeling", Fourth International Conference on Intelligence Science (ICIS2020), Durgapur, India, 24-27 Feb 2021.

    [J55] H. Xue, B.-M. Batalden, P. Sharma, J. A. Johansen, D. K. Prasad, "Biosignals based driving skill classification using machine learning: a case study of maritime navigation", Applied Sciences, vol. 11, issue 20,  article id. 9765, 2021.(PDF)

    [J54] D. Singh, A. Somani, A. Horsch, D. K. Prasad, "T-MIS: Transparency Adaptation in Medical Image Segmentation", Nordic Machine Intelligence, vol. 1, issue 1, pp. 11-13, 2021. (PDF)

    Year 2020
     
    [J53] F. Stroehl, S. Jadhav, B. S. Ahluwalia, K. Agarwal, D. K. Prasad. "Object detection neural network improves Fourier ptychography reconstruction", Optics Express, vol. 28, issue 25, pp. 37199-37208, 2020. 

    [J52] A. Butola, S. R. Kanade, S. Bhatt, V. K. Dubey, A. Kumar, A. Ahmad, D. K Prasad, P. Senthilkumaran, B. S. Ahluwalia, D.  S. Mehta. "High space-bandwidth in quantitative phase imaging using partially spatially coherent optical coherence microscopy and deep neural network", Optics Express, vol. 28, issue 24, pp 36229-36244, 2020. 

    [J51] R. pal, A.A. Sekh, S. Kar, and D.K. Prasad, "Neural network based country wise risk prediction of COVID-19," Applied Sciences, vol. 10, issue18, article id 6448, 2020. (source code and Project page)

    [J50] H. Dong, D.K. Prasad, I.-M. Chen. "Object Pose Estimation via Pruned Hough Forest with Combined Split Schemes for Robotic Grasp", IEEE Transactions on Automation Science and Engineering, 2020. 

    [C37] A. Singh, A. Bhave, and D.K. Prasad, "Single image dehazing for a variety of haze scenarios using back projected pyramid network", ECCV Workshops, 2020.(Source code)

    [J49] A. Butola, D. Popova, D. K. Prasad, A. Ahmad, A. Habib, J. C. Tinguely, P. Basnet, G. Acharya, P. Senthilkumaran, D. S. Mehta, B. S. Ahluwalia. "High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition", Scientific Reports, vol. 10, issue 1, pp. 1-12, 2020. 

    [J48] D. K. Prasad, H. Dong, D. Rajan,  and C. Quek, "Are object detection assessment criteria ready for maritime computer vision?," IEEE Transactions on Intelligent Transportation Systems, vol. 21, issue12, pp. 5295-5304, 2019. (Singapore Maritime dataset and Project page)

    [J47] A. A. Sekh, D. P. Dogra, S. Kar, P. P. Roy, and D. K. Prasad, “Can We Automate Diagrammatic Reasoning?,” Pattern Recognition, vol. 106, article id 107412, 2020. 

    [C36] A.A. Sekh, I-S. Opstad, A.B. Birgisdottir, T. Myrmel, B.S. Ahluwalia, K. Agarwal, and D. K. Prasad, “Learning nanoscale motion patterns of vesicles in living cells,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Washington, USA, 14-19 June, 2020. (Google Scholar H5 index= 240)(Project page and dataset)

    [C36] S.-W. Pang, C. Quek, and D. K. Prasad, “GEMM-eMFIS (FRI/E): A Novel General Episodic Memory Mechanism for Fuzzy Neural Networks,” International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 19-24 July, 2020.

    [J46] S. Dey, A. K. Singh, D. K. Prasad, and M.-M. Klaus, "IRON-MAN: Temporal Motionless Analysis of Video using CNN in MPSoC", IEEE Access, vol. 8, pp. 137101-137115, 2020.

    [C36] S. Dey, A. K. Singh, D. K. Prasad, and M.-M. Klaus, "Temporal Motionless Analysis of Video using CNN in MPSoC", IEEE International Conference on. Application-specific Systems, Architectures and Processors (ASAP 2020),Manchester, UK, 6-8 Aug 2020.

    [J45] F Liu, A.A. Sekh, C Quek, G.S. Ng, and D.K. Prasad, "RS-HeRR: A Rough Set based Hebbian Rule Reduction Neuro-Fuzzy System", Neural Computing and Applications, vol. 33, pp. 1123-1137, 2021. 

    [J44] A. A. Sekh, D. P. Dogra, S. Kar, P. P. Roy, and D. K. Prasad, “ELM-HTM Guided Bio-inspired Unsupervised Learning for Anomalous Trajectory Classification,” Cognitive Systems Research, vol. 63, pp. 30-41, 2020. 

    [J43] M. Ashrafi, D. K. Prasad, and C. Quek "IT2-GSETSK: An Evolving Interval Type-II TSK Fuzzy Neural System for Online Modeling of Noisy Data", Neurocomputing, vol. 407, pp. 1-11,  2020. (Source code)

    [J42] A.Butola, D. K. Prasad, A. Ahmad, V. Dubey, D. Qaiser, A. Srivastava, P. Senthilkumaran, B. S. Ahluwalia, and D. S. Mehta. "Deep learning architecture LightOCT for diagnostic decision support using optical coherence tomography images of biological samples.", Biomedical Optics Express, vol. 11, issue 9, pp. 5017-5031, 2020. (Source code, pretrained model and AIIMS Dataset related to this paper)

    [J41] M.C. Leong, D. K. Prasad, Y. T. Lee, and F. Lin. "Semi-CNN Architecture for Effective Spatio-Temporal Learning in Action Recognition.", Applied Sciences, vol. 10, issue 2 article id 557, 2020. (source code and Project page)

    [J40] P. K. Roy, H Mondal, A Mallick, D.K. Prasad. "Inverse and efficiency of heat transfer convex fin with multiple non-linearities", Heat Transfer, vol. 50, issue1, pp. 158-178, 2020. 

    [B03] M. Ramaiah and D. K. Prasad, "Polygonal approximation of digital planar curve using novel significant measure," Parallel Manipulators,  Serdar Küçük(Ed.), InTech, 2020.  Available here InTech

    Year 2019

    [J39] S. Dey, A. K. Singh, D. K. Prasad, and M.-M. Klaus, "SoCodeCNN: Program Source Code for Visual CNN Classification Using Computer Vision Methodology", IEEE Access,  vol. 7, pp. 157158-157172, 2019.(PDF)(SoCodeCNN Source code) (Pixelator source code link)

    [J38] G. Tripathi, H. Anowarul, K. Agarwal, and D. K. Prasad, "Classification of Micro-Damage in Piezoelectric Ceramics Using Machine Learning of Ultrasound Signals", Sensors, Vol. 19, Issue 19, Article id 4216, 2019.(PDF)

    [J37] K. Kansal, A. V. Subramanyam, D. K. Prasad, and M. Kankanhalli, "CARF-Net: CNN Attention and RNN Fusion Network for Video based Person Re-identification", Journal of Electronic Imaging,  vol. 28, issue 2, article id 023036, 2019.

    [J36] H. Dong, C. Qiu, D.K. Prasad, Y. Pan, J. Dai, and I.M. Chen, "Enabling grasp action: Generalized quality evaluation of grasp stability via contact stiffness from contact mechanics insight", Mechanism and Machine Theory, vol. 134, pp. 625-644, 2019.
     
    [J35] H. Dong, E. Asadi, G. Sun, D. K. Prasad, and I-Ming Chen, "Real-time Robotic Manipulation of Cylindrical Objects in Dynamic Scenarios through Elliptic Shape Primitives,” IEEE Transactions on Robotics, vol.35, issue 1, pp. 95-113, 2019, (YouTube demo link)

    [J34] A. Mallick, R. Ranjan, and D. K. Prasad, "Inverse estimation of variable thermal parameters in a functionally graded annular fin using dragon fly optimization," Inverse Problems in Science and Engineering, vol. 27, issue 7, pp. 969-986, 2019. 

    [J33] A. Mallick, D. K. Prasad, P. P. Behera, "Stresses in radiative annular fin under thermal loading and its inverse modeling using Sine Cosine Algorithm (SCA)," Journal of Thermal Stresses, vol. 42, issue 4, pp. 401-415, 2019. 

    [C33] S.AA. Maldonado; G.M. A Mehdi Hussain, F. Godtliebsen, B.S. Ahluwalia, H.H. Phuong; D.K. Prasad, K. Agarwal, "Multiple Signal Classiflcation: Challenges on the Route from Millimeter Resolution to Nanometer Resolution," PIERS2019, Rome, Italy 17-20 June 2019.

    [C32] H. Mahawar, K. Agarwal, D.K. Prasad, F. Melandso, and A. Habib, “Subsurface defect imaging in PZT ceramics using dual point contact excitation and detection,” Symposium on UltraSonic Electronics(USE 2019), Osaka, Japan, 25-27 November, 2019.

    Year 2018

    [J32] H. Dong, G. Sun, W.-C. Pang, E. Asadi, D. K. Prasad, and I-Ming Chen, "Fast ellipse detection via gradient information for robotic manipulation of cylindrical objects,” IEEE Robotics and Automation Letters, vol.3, issue 4, pp. 2754-2761, 2018. 

    [J31] D. K. Prasad, C.K. Prasath, D. Rajan, L. Rachmawati, E. Rajabally, and C. Quek, "Object detection in maritime environment: Performance evaluation of background subtraction methods," IEEE Transactions on Intelligent Transportation Systems,  vol. 20, issue 5 pp. 1787-1802, 2018.  (Singapore Maritime dataset and Project page)

    [J30] H. Dong,  D. K. Prasad, and I-Ming Chen, “Accurate detection of ellipses with false detection control at video rates using a gradient analysis,” Pattern Recognition, vol. 81, pp. 112-130, 2018.(online link)

    [J29] D. K. Prasad, S. Liu, S.-H. A. Chen, and C. Quek, "Sentiments Analysis Using EEG Activities for Suicidology,"  Expert Systems with Applications , vol. 103, pp. 206-217, 2018.(NTUSS dataset size:1.06GB)

    [J28] K. Agarwal, R. Machan, and D. K. Prasad, “Non-heuristic automatic techniques for overcoming low signal-to-noise-ratio bias of localization microscopy and multiple signal classification algorithm”, Scientific Reports, vol. 8, article id 4988, 2018. (PDF )

    [J27] A. R. Iyer, D.K. Prasad, and C. Quek, "PIE-RSPOP: A brain-inspired Pseudo-Incremental Ensemble Rough Set Pseudo-Outer Product Fuzzy Neural Network", Expert Systems With Applications , vol. 95, issue 4, pp. 172-189, 2018. (online link)

    [C31] H. Dong, D. K. Prasad, Q.Yuan, J.Zhou, E.Asadi, I-Ming Chen," Efficient Pose Estimation from Single RGB-D Image via Hough Forest with Auto-context ,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October, 1-5, 2018. 

    [C30] H. Dong, G.Sun, W.-C.Pang, E.Asadi, D.K.Prasad, I-Ming Chen, "Fast Ellipse Detection for Robotic Manipulation of Cylindrical Objects,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October, 1-5, 2018. 

    [C29] A. Mallick, D. K. Prasad, and P. P. Behera. "Thermo-mechanical analysis of a radiative annular fin." AIP Conference Proceedings. Vol. 1988. No. 1., 2018.

    Year 2017

    [J26] K. Agarwal and D.K. Prasad, "Eigen-analysis reveals components supporting super-resolution imaging of blinking fluorophores", Scientific Reports, vol. 7, article id 4445, 2017.(Source code)(PDF)

    [J25] D. K. Prasad, D. Rajan, L. Rachmawati, E. Rajabally, and C. Quek, "Video Processing from Electro-optical Sensors for Object Detection and Tracking in Maritime Environment: A Survey," IEEE Transactions on Intelligent Transportation Systems, vol. 18, issue 8, pp. 1993-2016, 2017. (Singapore Maritime dataset and Project page) (preprint PDF)

    [J24] R. Ranjan, A. Mallick, and D. K. Prasad, "Closed form solution for a conductive-convective-radiative annular fin with multiple nonlinearities and its inverse analysis,"  Heat and Mass Transfer, vol. 53, issue 3, pp. 1037-1049, 2017. 

    [C28] H. Dong, I-Ming Chen, and D. K. Prasad, “Robust Ellipse Detection Via Duality Principle With A False Determination Control,” International Conference on Computer Vision and Image Processing, Noida, India, 9-12 September, 2017.

    [C27] H. Dong, I-Ming Chen, and D. K. Prasad, “Robust Ellipse Detection Via Arc Segmentation And Arc Classification,” International Conference on Image Processing (ICIP), Beijing, China, 17-20 September, 2017.

    [C26] D. K. Prasad, C.K. Prasath, D. Rajan, L. Rachmawati, E. Rajabally, and C. Quek, “Maritime situational awareness using adaptive multisensory management under hazy conditions,” 5th International Maritime-Port Technology and Development Conference (MTEC 2017), Singapore, 26-28 April, 2017.

    [J23] D. K. Prasad, C.K. Prasath, D. Rajan, C. Quek, L. Rachmawati, and  E. Rajabally, “Challenges in video based object detection in maritime scenario using computer vision,” International Journal of Computer and Information Engineering, vol. 11, issue 1, pp. 31-36, 2017. ( It was accepted at 19th International Conference on Connected Vehicles, Zurich, 13-14 January, 2017. This paper had received the "Best Paper Award" so it was selected for the next issue of the IJCIE journal).

    Year 2016

    [J22] D. K. Prasad, D. Rajan, L. Rachmawati, E. Rajabally, and C. Quek, “MuSCoWERT: multi-scale consistence of weighted edge Radon transform for horizon detection in maritime images,”  Journal of Optical Society America A, vol. 33, issue 12, pp. 2491-2500, 2016.(source code, dataset and Project page)(PDF)

    [J21] D. K. Prasad and K. Agarwal, “Classification of hyperspectral or trichromatic measurements of ocean color data into spectral classes”, Sensors, 16(3),pp. 413, 2016. (PDF)(sourcecode , filesize- 590KB) (sourcecode with sample data, filesize - 2.13 GB)

    [J20] A. Mallick, R. Ranjan, D. K. Prasad and Ranjan Das, "Inverse Prediction and Application of Homotopy Perturbation Method for Efficient Design of an Annular Fin with Variable Thermal Conductivity and Heat Generation", Mathematical Modelling and Analysis, vol. 21, issue 5. pp. 699-717, 2016. 

    [C25] D. K. Prasad,  “Strategies For Resolving Camera Metamers using 3+1 channel,” IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Las Vegas, USA, 26 June – 1 July, 2016. (PDF)

    [C24] D. K. Prasad, D. Rajan, C. Krishna Prasath, L. Rachmawati, E. Rajabally, and C. Quek, “MSCM-LiFe: Multi-Scale Cross Modal Linear Feature for Horizon Detection in Maritime Images,”  IEEE TENCON, Singapore,22-25 Nov, 2016.  (source code)

    Year 2015

    [J19] D. K. Prasad and L. Wenhe, “Metrics and statistics of frequency of occurrence of metamerism in consumer cameras for natural scenes”  Journal of Optical Society America A,vol. 32, issue 7, pp. 1390-1402, 2015. (NUS Hyperspectral dataset)

    [J18] D. K. Prasad , “Gamut expansion of consumer camera to the CIE XYZ color gamut using a specifically designed fourth sensor channel”  Applied Optics ,vol. 54, issue 20, pp. 6146-6154, 2015. 

    [J17] R. Das and D. K. Prasad, “ Prediction of Porosity and Thermal Diffusivity in a Porous Fin using Differential Evolution Algorithm,” Swarm and Evolutionary Computation, vol 23, pp. 27-39, 2015. 

    [C23] R. Das and D. K. Prasad, Application of hybrid optimization algorithm for solving inverse problem in cylindrical fin, 7th International Conference on Computational Intelligence, Modelling and Simulation (CIMSim2015), Kuantan, Malaysia, 2015. 

    Year 2014

    [J16] D. K. Prasad, M. K.H. Leung, C. Quek and Michael S. Brown, “DEB: Definite error bounded tangent estimator for digital curves,”  IEEE Transactions on Image Processing, vol. 23, issue 10, pp. 4297-4310, 2014.(Matlab Source Code) 

    [C22] N. Rang, D. K. Prasad, and M. S. Brown, “Training-Based Spectral Reconstruction from a Single RGB Image,” European Conference on Computer Vision (ECCV 2014), Zurich, Switzerland, 6-12 Sept, 2014. (Project page)

    [C21] N. Rang, D. K. Prasad, and M. S. Brown, “Raw-to-raw: Mapping between image sensor color responses,” IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Ohio, USA, 24-27 June, 2014. (PDF) (Demo Raw-to-Raw)

    [J15] D. Cheng, D. K. Prasad, and Michael S. Brown, “On Illuminant Estimation:Why spatial domain methods work and the role of the color distribution,”  Journal of Optical Society America A, vol. 31, issue 5, pp. 1049-1058, 2014.(PDF) (Project page) (Dataset)

    [J14] D. K. Prasad, and M. S. Brown, “Design of macro-filter-lens with simultaneous chromatic and geometric aberration correction,”  Applied Optics,  vol. 53, issue 1, pp. 32-37, 2014. (PDF)

    Year 2013

    [J13] D. K. Prasad, “Fabrication imperfection analysis and statistics generation using precision and reliability optimization method,”  Optics Express, vol. 21, issue 15, pp.17602-17614, 2013. (PDF)

    [J12] D. K. Prasad, and M. S. Brown, “Online tracking of deformable objects under occlusion using dominant points,”  Journal of Optical Society America A, vol. 30, issue 8, pp.1484-1491, 2013. (Matlab Source codes) 

    [J11] D. K. Prasad, M. K.H. Leung and C. Quek, “ElliFit: An unconstrained, non-iterative, least squares based geometric Ellipse Fitting method,”  Pattern Recognition, vol. 46, issue 5, pp. 1449-1465, 2013. (PDF) (Matlab Source Code)(OpenCV source code by Harish(dot)Venkatesan[at]colorado(dot)edu)(Eigen3 ported code to Hulk by nicolas.riebesel[at]tuhh.de) 

    C20. D. K. Prasad, N. Rang,  and M. S. Brown, “Quick Approximation of Camera’s Spectral Response From Casual Lighting,” IEEE International Conference on Computer Vision Workshops (ICCVW 2013), Sydney, Australia, 1-8 December, 2013. (PDF) (Results)

    [C19] D. K. Prasad and C. Quek, “Comparison of error bounds for non-parametric dominant point detection,” Ninth International Conference on Information, Communications, and Signal Processing (ICICS 2013), Tainan, Taiwan, 10-13 December, 2013. 

    [J10] A. Bowmik, R.K. Singla, P.K. Roy, D.K. Prasad, R. Das and R. Repaka, "Predicting geometry of rectangular and hyperbolic fin profiles with temperature-dependent thermal properties using decomposition and evolutionary methods," Energy Conversion & Management , vol. 74, pp. 535-547, 2013. 

    [J09] D. K. Prasad, “PRO: A novel approach to precision and reliability optimization based dominant point detection,”  Journal of Optimization, vol. 2013, Article ID 345287, 15 pages, 2013.(PDF)

    [J08] D. K. Prasad, “Rise of International Schools in India,”  International Journal of Education Economics and Development, vol. 4, no. 2, pp. 190-201, 2013. 

    Year 2012

    [J07] D. K. Prasad, M. K.H. Leung, C. Quek, and S.-Y. Cho, “A novel framework for making dominant point detection methods non-parametric,” Image and Vision Computing, vol. 30, issue 11, pp. 843-859, 2012.(PDF) (dataset link) (source code for parameer independent RDP -  Matlab code: OpenCV(C#,VB.Net) code )

    [J06] D. K. Prasad, M. K.H. Leung and S.-Y. Cho, “Edge curvature and convexity based ellipse detection method,”  Pattern Recognition, vol. 45, issue 9, pp. 3204-3221, 2012.(PDF) (list of 400 Real Images Caltech256)  (Ellipse Labeling Tool) 

    [J05] D. K. Prasad, “Survey of The Problem of Object Detection In Real Images,”  International Journal of Image Processing, vol. 6, issue 6, pp. 441-466, 2012. (PDF)

    [J04] D. K. Prasad, “Assessing Error Bound For Dominant Point Detection,”  International Journal of Image Processing, vol. 6, issue 5, pp. 326-333, 2012. (PDF) 

    [J03] D. K. Prasad, C. Quek, and M. K.H. Leung, “Fast Segmentation of Sub-Cellular Organelles,”  International Journal of Image Processing, vol. 6, issue 5, pp. 317-325, 2012.(PDF) 

    [J02] D. K. Prasad, “High Availability based Migration Analysis to Cloud Computing for High Growth Businesses,” International Journal of Computer Networks, vol. 4, issue 2, 2012. (PDF)   

    [C18] D. K. Prasad, C. Quek, and M. K.H. Leung, “A precise ellipse fitting method for noisy data,” International Conference on Image Analysis and Recognition (ICIAR 2012), Aveiro, Portugal, 25-27 June, 2012.  (PDF)

    [C17] D. K. Prasad, C. Quek, and M. K.H. Leung, “A non-heuristic dominant point detection based on suppression of break points,” International Conference on Image Analysis and Recognition (ICIAR 2012), Aveiro, Portugal, 25-27 June, 2012. (PDF)

    [B02] D. K. Prasad and M. K. H. Leung, "Polygonal Representation of Digital Curves," Digital Image Processing, Stefan G. Stanciu (Ed.),  InTech, 2012.  Available here InTech  (Matlab source code)

    [B01]  D. K. Prasad and M. K.H. Leung, "Methods for ellipse detection from edge maps of real images"  in Machine Vision - Applications and Systems, Fabio Solari, Manuela Chessa and Silvio P. Sabatini (Ed.),  InTech, 2012. Available here InTech 

    Year 2011

    [J01] J. A. Starzyk and D. K. Prasad, “A Computational Model on Machine Consciousness”, International Journal of Machine Consciousness (World Scientific), vol. 3, issue 2,pp. 255-281, 2011.(PDF)  

    [C16] D. K. Prasad, C. Quek, M. K.H. Leung, and S.-Y. Cho, “A parameter independent line fitting method,” 1st IAPR Asian Conference on Pattern Recognition (ACPR 2011), Beijing, China, 28-30 Nov, 2011.(acceptance rate:146/272 ~53.4%) (Google Scholar H5 index= 12) (PDF)(ppt) ( Matlab Source code) (OpenCV source code by Chris Hemmings (SPI Global, Manila, Philippines)

    [C15] D. K. Prasad, “Adaptive traffic signal control system with cloud computing based online learning,” Eighth International Conference on Information, Communications, and Signal Processing (ICICS 2011), Singapore, 13-16 December, 2011. (PDF)

    [C14] D. K. Prasad, R. K. Gupta and M. K.H. Leung, “An error bounded tangent estimator for digitized elliptic curves,” 16th IAPR International Conference on Discrete Geometry for Computer Imagery (DGCI 2011), Nancy, France, 6-8 April, 2011. (PDF)

    Year 2010

    [C13] D. K. Prasad and M. K.H. Leung, “An ellipse detection method for real images,” 25th International Conference of Image and Vision Computing New Zealand (IVCNZ 2010), Queenstown, New Zealand, 8-9 November, 2010.(PDF)

    [C12] D. K. Prasad and M. K.H. Leung, “Error Analysis of Geometric Ellipse Detection Methods due to Quantization”, Fourth Pacific-Rim Symposium on Image and Video Technology (PSIVT 2010), Singapore, 14-17 November, 2010. (PDF) (poster)

    [C11] D. K. Prasad and M. K.H. Leung, “An error bounded tangent estimator for digital curves,” 25th International Conference of Image and Vision Computing New Zealand (IVCNZ 2010), Queenstown, New Zealand, 8-9 November, 2010.(poster) (PDF)

    [C10] D. K. Prasad and M. K.H. Leung, “Reliability/Precision Uncertainty in Shape Fitting Problems”, IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, 26-29 September, 2010. (Google Scholar H5 index= 45) (pdf)

    [C09] D. K. Prasad  and M. K.H. Leung, “Clustering of Ellipses based on their Distinctiveness: An aid to Ellipse Detection Algorithms”, 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT 2010), Chengdu, China, 9-11 July, 2010.(pdf)(source code)

    [C08] D. K. Prasad and M. K.H. Leung, “A Hybrid Approach for Ellipse Detection in Real Images”, 2nd International Conference on Digital Image Processing (ICDIP 2010), Singapore, 26-28 February, 2010.(pdf)

    [C07] J. A. Starzyk and D. K. Prasad, “Machine Consciousness: A Computational Model”, Third International ICSC Symposium on Models of Consciousness, BICS 2010, Madrid, Spain, 14-16 July, 2010.(pdf) (ppt)

    [C06] D. K. Prasad and J. A. Starzyk, “A Perspective on Machine Consciousness” , Second International Conference on Advanced Cognitive Technologies and Applications, COGNITIVE 2010, Lisbon, Portugal, 21-26 November, 2010.(pdf)

    [C05] D. K. Prasad and J. A. Starzyk, “Object detection and representation in motivated conscious machines,” Decade of the Mind – VI, Singapore, 18-20 October, 2010.(poster)(3 Page Abstract & poster only)

    [C04] D. K. Prasad and C. K. Prasath, “Reconfigurable Virtual Platform for Real Time Kernel” , 9th USENIX Symposium on Operating System Design and Implementation (OSDI 2010), Vancouver, BC, Canada, 4-6 October, 2010.(ppt) (one page abstract, poster & demo only)

    [C03] C. K. Prasath and D. K. Prasad, “Design and Development of a Reconfigurable Virtual Platform for Real Time Kernel” , Second International Conference on Software Technology and Engineering (ICSTE 2010), San Juan, Puerto Rico, USA, 3-5 October, 2010. (oral paper) (pdf)

    Year 2009

    [C02] D. K. Prasad, “Application of Image Composition Analysis for Image Processing”, IMI International Workshop on Computational Photography and Aesthetics, Singapore, 12-13 December, 2009.(poster) (One page abstract & poster only)

    [C01] D. K. Prasad, Chai H. Quek, and Maylor K.H. Leung, “A Hybrid Approach for Breast Tissue Data Classification”, IEEE  TENCON 2009, Singapore, 23-26 November, 2009.(pdf) 

     

    Research interests

    • Sustainable AI
    • Scalable AI
    • Interpretable AI
    • Generative AI
    • Application of AI for life sciences.

    Teaching

    INF-3910-7 Computational Intelligence and its Applications

    INF-1101 Data structures and algorithms

    INF-2202 Concurrent and Data-Intensive Programming

    INF-2220 Cloud computing and big data technology

    INF-2200 Artificial Intelligence II

    INF-3605/8605 Interpretability in Deep Learning

    INF-8606 Generaitve AI in Life Sciences

    Researcher profile in Cristin
    ResearchGate
    ORCID: http://orcid.org/0000-0002-3693-6973

    Member of research group

    Computational Analytics and Intelligence (CAI)   English content

    Member of project

    VirtualStain    English content NanoAI    English content NanoAI VirtualStain OrganVision

    CV

    Dilip K. Prasad (IEEE Senior Member) is a Professor at the Department of Computer Science, UiT The Arctic University of Norway. He received the Ph.D and B.Tech degree in Computer Science and Engineering from Nanyang Technological University, Singapore and Indian Institute of Technology (Indian School of Mines), Dhanbad, India respectively. He was a senior research fellow at Nanyang Technological University, Singapore from 2015-2019 and research Fellow at National University of Singapore from 2012-2015. Prior to Ph.D., he has worked for 5 years with IBM, Infosys, Mediatek and Philips.He has been selected as a Fellow for Kauffman Global Scholarship in 2011, in which he was trained in entrepreneurship at Harvard University, MIT, Stanford University and the Kauffman Foundation. He has been awarded with Rolls-Royce Inventer Award in 2016. He has published 130+ internationally peer-reviewed research articles. His current research interests include image processing, machine learning and artificial intelligence. He has been a reviewer for more than 60 journals and 30+ conferences including CVPR, ICCV, ECCV, NIPS, AAAI, BMVC, WACV, ACCV, etc. He is area chair for NeurIPS 2022-23. He is a organizer chair for ICCV Workshop 2023 for "Resource Efficient Deep Learning".

    For more academic details, my research team source code, my team research project page on website - Website

    Google Scholar Citations

    Publons profile