Current | People | PhD Students | PostDoc
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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Nauman Fazal
Research Associate | AI & Computer Vision Expert | Deep Learning & Machine Learning Specialist | Full Stack Developer | Web Scraping and Automation Enthusiast Nauman Fazal is a skilled full-stack developer with expertise in machine learning, computer vision, and web development. With proficiency in languages such as Python, TypeScript, and frameworks like React, Angular,…
IEEETGRS2024 – Stereollax Net: Stereo Parallax Based Deep Learning Network For Building Height Estimation
Sana Jabbar and Murtaza Taj Abstract: Accurate estimation of building heights is crucial for effective urban planning and resource management as it provides essential geometric information about the urban landscape. Many end-to-end deep learning-based networks have been proposed for image-to-height mapping using high-resolution nonoptical and optical remote sensing imagery. In this study, we develop a…
Muhammad Muqsit Islam
Research Associate | Full Stack Developer | Web Scraping and Automation Expert | Certified DL & ML Specialist Muhammad Muqsit Islam is a full-stack developer proficient in Web Development, Computer Vision, and Deep Learning. They are skilled in Django, Django Rest Framework, React, Flask, TensorFlow, Docker and other technologies, effectively bridging the gap between frontend…
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…
Summer Internships 2018
The Computer Vision Lab hosted a rigorous summer internship program for undergraduate students. Sophomore, Junior and Senior interns worked for 2 months in the lab, under the supervision of faculty and PhD students. The students worked both individually and in groups, on a range of ideas, from making a campus 3D model to automatic generation…