murtaza
murtaza's Latest Posts
Paper accepted at ICPR 2022
Our paper titled “Neural Network Pruning Through Constrained Reinforcement Learning” accepted at ICPR 2022. This work was an outcome of MS Thesis by Shehryar Malik More info: Click here
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 […]
Sohaib Masood Rabbani
Sohaib Masood Rabbani is an MS-CS student at LUMS and a Graduate Research Assistant at Computer Vision and Graphics Lab (CVGL), LUMS Syed Babar Ali School of Science and Engineering. He earned his undergraduate degree from NUCES-FAST in Computer Science. Currently, he is working on Disease Classification and Localization on Chest X-Rays through deep learning. […]
Paper accepted at ICASSP 2022
Our paper titled “Camera Calibration through Camera Projection Loss” accepted at ICASSP 2022. This work was an outcome of MS Thesis by Talha Hanif Butt More info: Click here
Camera Calibration through Camera Projection Loss
Talha Hanif Butt, Murtaza Taj Abstract: Camera calibration is a necessity in various tasks including 3D reconstruction, hand-eye coordination for a robotic interaction, autonomous driving, etc. In this work we propose a novel method to predict extrinsic (baseline, pitch, and translation), intrinsic (focal length and principal point offset) parameters using an image pair. Unlike existing […]
Paper accepted at BMVC 2021
Our paper titled “Teacher-Class Network: A Neural Network Compression Mechanism” accepted at BMVC 2021. This work was an outcome of MS Thesis by Shaiq Munir More info: Click here
Teacher-Class Network: A Neural Network Compression Mechanism
Shaiq Munir Malik, Fnu Mohbat, Muhammad Umair Haider, Muhammad Musab Rasheed and Murtaza Taj Abstract: To reduce the overwhelming size of Deep Neural Networks, teacher-student techniques aim to transfer knowledge from a complex teacher network to a simple student network. We instead propose a novel method called the teacher-class network consisting of a single teacher […]
Shehryar Malik
Shehryar Malik is a MS Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
2xPapers accepted at ICIP 2021
Two of our papers accepted at ICIP 2021 1. “Spatio-Temporal Crop Classification On Volumetric Data”, More info: Click here 2. “Comprehensive Online Network Pruning via Learnable Scaling Factors”, More info: Click here
Spatio-Temporal Crop Classification On Volumetric Data
M. U. Qadeer, S. Saeed, M. Taj and A. Muhammad Abstract: Large-area crop classification using multi-spectral imagery is a widely studied problem for several decades and is generally addressed using classical Random Forest classifier. Recently, deep convolutional neural networks (DCNN) have been proposed. However, these methods only achieved results comparable with Random Forest. In this […]
