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Usman Nazir
Usman Nazir is a PhD Student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
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MICCAI2025 – CATVis: Context-Aware Thought Visualization
Tariq Mehmood*, Hamza Ahmad*, Muhammad Haroon Shakeel, Murtaza Taj (* contributed equally) Abstract: EEG-based brain-computer interfaces (BCIs) have shown promise in various applications, such as motor imagery and cognitive state monitoring. However, decoding visual representations from EEG signals remains a significant challenge due to their complex and noisy nature. We thus propose a novel 5-stage…
ICPR2022 – Neural Network Pruning Through Constrained Reinforcement Learning
Shehryar Malik, Muhammad Umair Haider*, Omer Iqbal, Murtaza Taj Abstract: Network pruning reduces the size of neural networks by removing (pruning) neurons such that the performance drop is minimal. Traditional pruning approaches focus on designing metrics to quantify the usefulness of a neuron which is often quite tedious and sub-optimal. More recent approaches have instead…
IEEE TGRS – A Residual-Dyad Encoder Discriminator Network for Remote Sensing Image Matching
Numan Khurshid, Mohbat Tharani, Murtaza Taj, and Faisal Qureshi Abstract: We propose a new method for remote sensing image matching. The proposed method uses encoder subnetwork of an autoencoder pre-trained on GTCrossView data to construct image features. A discriminator network trained on University of California Merced Land Use/Land Cover dataset (LandUse) and High-resolution Satellite Scene…
ICIP2021 – Spatio-Temporal Crop Classification On Volumetric Data
M. U. Qadeer, S. Saeed, M. Taj and A. Muhammad Abstract: Large-area crop classification using multi-spectral imagery is a widely studied problem for several decades and is generally addressed using classical Random Forest classifier. Recently, deep convolutional neural networks (DCNN) have been proposed. However, these methods only achieved results comparable with Random Forest. In this…