Mohbat Tharani
Mohbat Tharani is a Research Assistant in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
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NCA2021 – Statistically Correlated Multi-task Learning for Autonomous Driving
Waseem Abbas, M. Fakhir Khan, Murtaza Taj, and Arif Mahmood Abstract Autonomous driving research is an emerging domain in computer vision and machine learning areas. Most existing methods perform Single Task Learning (STL) from one or more images while Multi-Task Learning (MTL) is more efficient due to the leverage of shared information between different tasks….
Fezan Rasool
Fezan Rasool is a PhD Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
MS Thesis Defense: Mohbat Tharani
Challenging the dogma of Relevance Feedback in Content based Image Retrieval Systems with Deep Learning May, 2018 at 3:00 pm in Smart Room 9-105 SBASSE. Abstract Association of images to their content based similar images in a database, is quite a fascinating challenge specially on social media platform where billions of tagged and untagged images…
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…
MS Thesis Defense: Muhammad Ahmed Bhimra
Spatio-Temporal Analysis of Landuse-Landcover Change Using Satellite Imagery Thursday 28 Feb, 2019 at 10:00 am in Smart Room 9-105 SBASSE. Abstract We propose an approach to recognize large scale, rapid spatio-temporal analysis of satellite remote sensing data. This technique can be used to measure longitudinal changes and yearly changes. Most of the existing methods either…