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AAAI2023 – Spatio-Temporal driven Attention Graph Neural Network with Block Adjacency matrix (STAG-NN-BA) for Remote Land-use Change Detection

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Usman Nazir, Wadood Islam, Sara Khalid, Murtaza Taj Abstract: Land-use monitoring is fundamental for spatial planning, particularly in view of compound impacts of growing global populations and climate change. Despite existing applications of deep learning in land use monitoring, standard convolutional kernels in deep neural networks limit the applications of these networks to the Euclidean…

BMVC2021 – Teacher-Class Network: A Neural Network Compression Mechanism
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BMVC2021 – Teacher-Class Network: A Neural Network Compression Mechanism

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Shaiq Munir Malik, Fnu Mohbat, Muhammad Umair Haider, Muhammad Musab Rasheed and Murtaza Taj Abstract: To reduce the overwhelming size of Deep Neural Networks, teacher-student techniques aim to transfer knowledge from a complex teacher network to a simple student network. We instead propose a novel method called the teacher-class network consisting of a single teacher…

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Sohaib Masood Rabbani

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Sohaib Masood Rabbani is an MS-CS student at LUMS and a Graduate Research Assistant at Computer Vision and Graphics Lab (CVGL), LUMS Syed Babar Ali School of Science and Engineering. He earned his undergraduate degree from NUCES-FAST in Computer Science. Currently, he is working on Disease Classification and Localization on Chest X-Rays through deep learning….

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ICIAP 2019 – Dimensionality Reduction Using Discriminative Autoencoders for Remote Sensing Image Retrieval

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Mohbat, Tooba Mukhtar, Numan Khurshid, and Murtaza Taj International Conference on Image Analysis and Processing (ICAIP), Trento, Itlay, September 9-13, 2019 Abstract Advancements in deep learning techniques caused a paradigm shift in feature extraction for image perception from handcrafted methods to deep methods. However, these deep features if learned through unsupervised methods bear large memory…

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M. Wadood Islam

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M. Wadood Islam was an MS-CS student at LUMS and a Graduate Research Assistant at Computer Vision and Graphics Lab (CVGL), LUMS Syed Babar Ali School of Science and Engineering. He earned his undergraduate degree from FAST-NUCES in Computer Science. His research interests include machine learning, deep learning, computer vision, and bioinformatics. He worked on classifying…

ICASSP 2019 – Using 3D Residual Network For Spatio-Temporal Analysis Of Remote Sensing Data
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ICASSP 2019 – Using 3D Residual Network For Spatio-Temporal Analysis Of Remote Sensing Data

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Muhammad Ahmed Bhimra, Usman Nazir, Murtaza Taj International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 12-17, 2019 Abstract In this paper, we propose an approach to recognize spatio-temporal changes from remote sensing data. Instead of performing independent analysis on each instance of satellite imagery, we proposed a 3D Convolutional Neural Network…

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