Browsing Institutt for datateknologi og informatikk by Author "Ullah, Mohib"

Now showing items 21-32 of 32

    • Objective and subjective quality assessment of 360-degree images 

      Sendjasni, Abderrezzaq (Doctoral theses at NTNU;2023:5, Doctoral thesis, 2023)
      360-degree images, a.k.a. omnidirectional images, are in the center of immersive media. With the increase in demands of the latter, mainly thanks to the offered interactive and immersive experience, it is paramount to ...

    • Optimized deep learning-based cricket activity focused network and medium scale benchmark 

      Ahmad, Waqas; Munsif, Muhammad; Ullah, Habib; Ullah, Mohib; Alsuwailem, Alhanouf Abdulrahman; Jilani Saudagar, Abdul Khader; Muhammad, Khan; Sajjad, Muhammad (Peer reviewed; Journal article, 2023)
      The recognition of different activities in sports has gained attention in recent years for its applications in various athletic events, including soccer and cricket. Cricket, in particular, presents a challenging task for ...

    • Optimized Deep-Learning-Based Method for Cattle Udder Traits Classification 

      Afridi, Hina; Ullah, Mohib; Nordbø, Øyvind; Alaya Cheikh, Faouzi; Larsgard, Anne Guro (Peer reviewed; Journal article, 2022)
      We propose optimized deep learning (DL) models for automatic analysis of udder conformation traits of cattle. One of the traits is represented by supernumerary teats that is in excess of the normal number of teats. ...

    • PedNet: A Spatio-Temporal Deep Convolutional Neural Network for Pedestrian Segmentation 

      Ullah, Mohib; Mohammed, Ahmed Kedir; Alaya Cheikh, Faouzi (Journal article; Peer reviewed, 2018)
      Articulation modeling, feature extraction, and classification are the important components of pedestrian segmentation. Usually, these components are modeled independently from each other and then combined in a sequential ...

    • S3AM: A Spectral-Similarity-Based Spatial Attention Module for Hyperspectral Image Classification 

      Li, Ningyang; Wang, Zhaohui; Alaya Cheikh, Faouzi; Ullah, Mohib (Peer reviewed; Journal article, 2022)
      Recently, hyperspectral image (HSI) classification based on deep learning methods has attracted growing attention and made great progress . Convolutional neural networks based models, especially the residual networks ...

    • Semi-supervised Network for Detection of COVID-19 in Chest CT Scans 

      Mohammed, Ahmed Kedir; Wang, Congcong; Zhao, Meng; Ullah, Mohib; Naseem, Rabia; Wang, Hao; Pedersen, Marius; Alaya Cheikh, Faouzi (Peer reviewed; Journal article, 2020)
      Deep Learning-based chest Computed Tomography (CT) analysis has been proven to be effective and efficient for COVID-19 diagnosis. Existing deep learning approaches heavily rely on large labeled data sets, which are difficult ...

    • Serious Games in Science Education. A Systematic Literature Review 

      Ullah, Mohib; Amin, Sareer Ul; Munsif, Muhammad; Safaev, Utkurbek; Khan, Habib; Khan, Salman Saeed; Ullah, Habib (Peer reviewed; Journal article, 2022)
      Teaching science through computer games, simulations, and artificial intelligence (AI) is an increasingly active research field. To this end, we conducted a systematic literature review on serious games for science education ...

    • SMDT-ReID: Self-supervised Multi-Object Detection, Tracking and Re-Identification 

      Moosa, Muhammad (Master thesis, 2024)
      Multi-Object Tracking (MOT) er fortsatt en kritisk utfordring i datasyn, spesielt i dynamiske og okkluderte miljøer. Denne oppgaverapporten presenterer et nytt rammeverk for MOT som avviker betydelig fra tradisjonelle ...

    • SMT: Self-supervised Approach for Multiple Animal Detection and Tracking 

      Moosa, Muhammad; Yamin, Muhammad Mudassar; Hashmi, Ehtesham; Beghdadi, Azeddine; Imran, Ali Shariq; Alaya Cheikh, Faouzi; Ullah, Mohib (IFIP Advances in Information and Communication Technology;, Chapter, 2024)
      In the domain of animal farming and wildlife management, monitoring animal behavior and movement is crucial. This paper proposes an efficient online multi-object tracking framework named SMT (Self-supervised Multi-animal ...

    • TCM: Temporal Consistency Model for Head Detection in Complex Videos 

      Khan, Sultan Daud; Altamimi, Ahmed Bder; Ullah, Mohib; Ullah, Habib; Alaya Cheikh, Faouzi (Peer reviewed; Journal article, 2020)
      Head detection in real-world videos is a classical research problem in computer vision. Head detection in videos is challenging than in a single image due to many nuisances that are commonly observed in natural videos, ...

    • Toward Authentication of Videos: Integer Transform Based Motion Vector Watermarking 

      Ullah, Rafi; Khan, Sultan Daud; Ullah, Mohib; Al Machot, Fadi; Ullah, Habib (Journal article; Peer reviewed, 2022)

    • Weaponized AI for cyber attacks 

      Yamin, Muhammad Mudassar; Ullah, Mohib; Ullah, Habib; Katt, Basel (Journal article; Peer reviewed, 2021)
      Artificial intelligence (AI)-based technologies are actively used for purposes of cyber defense. With the passage of time and with decreasing complexity in implementing AI-based solutions, the usage of AI-based technologies ...