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.
Talha Hanif Butt is a MS Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
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…
Shaiq Munir Malik is a MS Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
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…
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…
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…