Blar i forfatter "Ullah, Habib"

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    • AFSD: Adaptive Feature Space Distillation for Distributed Deep Learning 

      Khaleghian, Salman; Ullah, Habib; Johnsen, Einar Broch; Andersen, Anders; Marinoni, Andrea (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-08)
      We propose a novel and adaptive feature space distillation method (AFSD) to reduce the communication overhead among distributed computers. The proposed method improves the Codistillation process by supporting longer update interval rates. AFSD performs knowledge distillates across the models infrequently and provides flexibility to the models in terms of exploring diverse variations in the training ...

    • Deep Semisupervised Teacher–Student Model Based on Label Propagation for Sea Ice Classification 

      Khaleghian, Salman; Ullah, Habib; Kræmer, Thomas; Eltoft, Torbjørn; Marinoni, Andrea (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-14)
      In this article, we propose a novelteacher–student-based label propagation deep semisupervised learning (TSLP-SSL) method for sea ice classification based on Sentinel-1 synthetic aperture radar data. For sea ice classification, labeling the data precisely is very time consuming and requires expert knowledge. Our method efficiently learns sea ice characteristics from a limited number of labeled samples ...

    • IA-SSLM: Irregularity-Aware Semi-Supervised Deep Learning Model for Analyzing Unusual Events in Crowds 

      Aljaloud, Abdulaziz Salamah; Ullah, Habib (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-05-17)
      Analyzing unusual events is significantly important for video surveillance to ensure people safety. These events are characterized by irregular patterns that do not conform to the expected behavior in the surveillance scenes. We present a novel irregularity-aware semi-supervised deep learning model (IA-SSLM) for detection of unusual events. While most existing works depend on the availability ...

    • Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks 

      Khaleghian, Salman; Ullah, Habib; Kræmer, Thomas; Hughes, Nick; Eltoft, Torbjørn; Marinoni, Andrea (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-29)
      We explore new and existing convolutional neural network (CNN) architectures for sea ice classification using Sentinel-1 (S1) synthetic aperture radar (SAR) data by investigating two key challenges: binary sea ice versus open-water classification, and a multi-class sea ice type classification. The analysis of sea ice in SAR images is challenging because of the thermal noise effects and ambiguities ...