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Department of Physics and Technology salman.khaleghian@uit.no +4777644106 Tromsø FPARK E 330.1

Salman Khaleghian


PhD Student / Earth Observation


  • Salman Khaleghian, Habib Ullah, Thomas Kræmer, Nick Hughes, Torbjørn Eltoft, Andrea Marinoni :
    Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks
    Remote Sensing 2021 ARKIV / DOI
  • Salman Khaleghian, Habib Ullah, Thomas Kræmer, Torbjørn Eltoft, Andrea Marinoni :
    Deep Semisupervised Teacher–Student Model Based on Label Propagation for Sea Ice Classification
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 ARKIV / FULLTEKST / DOI
  • Desta Haileselassie Hagos, Theofilos Kakantousis, Vladimir Vlassov, Sina Sheikholeslami, Tianze Wang, Jim Dowling et al.:
    ExtremeEarth meets satellite data from space
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 ARKIV / DOI
  • Salman Khaleghian, Thomas Kræmer, Alistair Everett, Åshild Kiærbech, Nick Hughes, Torbjørn Eltoft et al.:
    Synthetic aperture radar data analysis by deep learning for automatic sea ice classification
    2021
  • Salman Khaleghian, Habib Ullah, Thomas Kræmer, Torbjørn Eltoft, Andrea Marinoni :
    A deep semi-supervised learning method based on transductive label propagation for sea/ice classification
    2021
  • Salman Khaleghian, Thomas Kræmer, Alistair Everett, Åshild Kiærbech, Nick Hughes, Torbjørn Eltoft et al.:
    Deep learning for enhanced sea ice understanding
    2020
  • Salman Khaleghian, Habib Ullah, Thomas Kræmer, Alistair Everett, Åshild Kiærbech, Joakim Pedersen et al.:
    Automatic sea ice classification using Synthetic aperture radar data analysis by deep learning
    2020

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

    Publications outside Cristin

    Salman Khaleghian, Habib Ullah, Thomas Kræmer, Torbjørn Eltoft, Andrea Marinoni, “Deep Semi-Supervised Teacher-Student Model based on Label Propagation for Sea Ice Classification”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing PP(99):1-1

    Desta Haileselassie Hagos, Theofilos Kakantousis, Vladimir Vlassov, Sina Sheikholeslami, Tianze Wang, Jim Dowling, Claudia Paris, Daniele Marinelli, Giulio Weikmann, Lorenzo Bruzzone, Salman Khaleghian, Thomas Kræmer, Torbjørn Eltoft, Andrea Marinoni, Despina-Athanasia Pantazi, George Stamoulis, Dimitris Bilidas, George Papadakis, George Mandilaras, Manolis Koubarakis, Antonis Troumpoukis, Stasinos Konstantopoulos, Markus Muerth, Florian Appel, Andrew Fleming, and Andreas Cziferszky.
    "ExtremeEarth Meets Satellite Data From Space."
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021

     

    Salman Khaleghian, Habib Ullah, Thomas Kræmer, Nick Hughes, Torbjørn Eltoft, Andrea Marinoni, “Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks”, Remote Sensing, 2021, 13(9).

    Salman Khaleghian, Habib Ullah, Thomas Kræmer, Torbjørn Eltoft, Andrea Marinoni, "A Noise-Aware Deep Learning Model for Sea Ice Classification Based on Sentinel-1 Sar Imagery", 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Pages 816-819.

    Manolis Koubarakis, George Stamoulis, Dimitris Bilidas, Theofilos Ioannidis, George Mandilaras, Despina-Athanasia Pantazi, George Papadakis, Vladimir Vlassov, Amir H. Payberah, Tianze Wang, Sina Sheikholeslami, Desta Haileselassie Hagos, Lorenzo Bruzzone, Claudia Paris, Giulio Weikmann, Daniele Marinelli, Torbjørn Eltoft, Andrea Marinoni, Thomas Kræmer, Salman Khaleghian, Habib Ullah, Antonis Troumpoukis, Nefeli Prokopaki Kostopoulou, Stasinos Konstantopoulos, Vangelis Karkaletsis, Jim Dowling, Theofilos Kakantousis, Mihai Datcu, Wei Yao, Corneliu Octavian Dumitru, Florian Appel, Silke Migdall, Markus Muerth, Heike Bach, Nick Hughes, Alistair Everett, Ashild Kiærbech, Joakim Lillehaug Pedersen, David Arthurs, Andrew Fleming, Andreas Cziferszky.” Artificial Intelligence and Big Data Technologies for Copernicus Data: The ExtremeEarth Project.” Conference on Big Data from Space (BiDS21) 2021. Virtual event, 18-20 May 2021.

    S. Khaleghian, T. Kræmer, A. Everett, Å. Kiærbech, N. Hughes, T. Eltoft, A. Marinoni, “Synthetic aperture radar data analysis by deep learning for automatic sea ice classification”, EUSAR, Leipzig, Germany, June 2021.

    Andrea Marinoni, Gianni C Iannelli, Salman Khaleghian, Paolo Gamba, “On the Optimal Design of Convolutional Neural Networks for Earth Observation Data Analysis by Maximization of Information Extraction”, IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium, 2020.

    T. Kræmer, S. Khaleghian, T. Eltoft, A. Marinoni, “Iceberg Detection in Sentinel-1 Extra Wide Swath Images: Deep Learning vs. Statistical Methods”, ESA Phi week, Frascati, Itally, 2019.

    Khaleghian, H.R. Rabiee, M.H. Rohban, “Face recognition across large pose variations via Boosted Tied Factor Analysis”, Applications of Computer Vision (WACV), 2011 IEEE Workshop on, p 190 – 195.

     Khaleghian, N. Taheri, R. Ebrahimpour, A. Hajiyani, 2008, “View-Independent Face Recognition with RBF Gating in Mixture of Experts Method by Teacher-Directed Learning”, International Joint Conferences on Computer Information and Systems Sciences and Engineering (CIS2E 08), Bridgeport University, USA, December 5-13.

    S. Khaleghian, A. M. Rahmani, M. R. Miryani, 2008, “A Hybrid Solution for load balancing in grid Environment with Attention to fault tolerance and Partitioning”, Science & research Branch Azad University, Computer conference, Tehran, Iran, 31 December.

    M. Miryani, M. Naghibzadeh, M. Kahani, S. Khaleghian, 2009, “Processors Determining to Satisfy Certain Objectives in the Hard Real-Time Systems”, The 2009 International Conference on Parallel and Distributed Processing Techniques and Applications, Monte Carlo Resort, Las Vegas, Nevada, USA, July 13-16.

    M. Miryani, S. Khaleghian, 2009: “Increasing CPU Utilization Using Main Memory Fuzzy Replacement Decision”, The 2009 International Conference on Genetic and Evolutionary Methods, Monte Carlo Resort, Las Vegas, Nevada, USA, July13-16.


    Research interests

    Big Data Analysis, Scalable Machine Learning, Distributed Deep Learning, Remote Sensing


    Member of research group



    FPARK E 330.1