Alumni | MS Students | People
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.
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Water Quality Assessment Using Visual Sensors
Mohbat Tharani, Abdul Wahab Amin, Fezan Rasool, Muhammad Maaz, Murtaza Taj, Abubakr Muhammad Summary In the absence of an effective trash management framework, trash is often illegally dumped in rivers and canals running through urban areas, contaminating freshwater and blocking drainage lines which result in urban floods. When this contaminated water reaches agricultural fields, it…
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…
Ijaz Akhter
Ijaz Akhter is a Ph.D. candidate in the Department of Computer Science, Lahore University of Management Sciences. Research Interests My research interests span the broad areas of Computer Vision and Graphics. More specifically I am interested in exploring the geometric properties of nonrigid object. The geometric relations between a camera and rigid world are well-known…
Alumni | MS Students | People
Umair Haider
Umair Haider is a MS Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
Localization Lens for Improving Medical Vision-Language Models
Hasan Farooq, Murtaza Taj, Mehwish Nasim, Arif Mahmood Abstract: Medical Vision-Language Models (Med-VLMs) have demonstrated strong capabilities in clinical tasks. However, they often struggle to understand anatomical structures and spatial positioning, which are crucial for medical reasoning. To address this, we propose a localization-aware enhancement to the Med-VLM pipeline, introducing improvements at three levels: data,…