M. Ahmed Bhimra
M. Ahmed Bhimra is a MS Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
M. Ahmed Bhimra is a MS Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
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…
Arif Mahmood successfully defended his Ph.D. at Lahore University of Management Sciences in May 2011. Dr. Mahmood’s research interests broadly span the areas of image processing and computer vision. More specifically, he is interested in optimization of image processing algorithms from computational perspective. He worked on fast image matching techniques and developed new bound based…
Tuberculosis Diagnosis in Medical Imagery using Deep Learning by Inam Ullah Taj Estimating labor population in Brick Kilns using Satellite Imagery and Remote Sensing by Muhammad Awais Ather Compressing neural networks via teacher assisted learning by Umair Haider Online structured filter pruning for neural networks by Shaiq Munir Malik Semantic Segmentation of water channel to…
Sohaib Khan is Associate Professor and Department Chair of Computer Science at LUMS School of Science and Engineering, Lahore, Pakistan. His research interests broadly span the areas of image and video analysis, including estimating 3D from images, motion capture and multiple camera surveillance systems. Dr Khan earned his PhD degree in Computer Science in 2002…
Ali Rehan was an MS student, doing his MS thesis with Computer Vision Lab from Jan 2011 – May 2012. He worked o n the Non-rigid Structure from Motion using Local Rigidity. His research was published at IEEE Winter Conference on Applications of Computer Vision (WACV) 2014. Please go to the project page for more…
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…