News and Events

Paper accepted at ICPR 2022

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

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Paper accepted at ICASSP 2022

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

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Paper accepted at BMVC 2021

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

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2xPapers accepted at ICIP 2021

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

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5xMS Thesis Proposal Defence

5xMS Thesis Proposal Defence

Tuberculosis Diagnosis in Medical Imagery using Deep Learning by Inam Ullah Taj Estimating labor population in Brick Kilns using Satellite Imagery and Remote Sensing by Muhammad Awais Ather Compressing neural networks via teacher assisted learning by Umair Haider Online structured filter pruning for neural networks by Shaiq Munir Malik Semantic Segmentation of water channel to […]

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3xPapers accepted at ICONIP 2019

3xPapers accepted at ICONIP 2019

Three papers have been accepted at “International Conference on Neural Information Processing – 19 (ICONIP-19)”. This conference is ranked A by the CORE rating measure and is going to be held from 12th to 15th December 2019 in Sydney, Australia. “Cross-view Image Retrieval – Ground to Aerial Image Retrieval through Deep Learning” “Patch-based Generative Adversarial Network […]

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Publications

Neural Network Pruning Through Constrained Reinforcement Learning

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 […]

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Camera Calibration through Camera Projection Loss

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 […]

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Teacher-Class Network: A Neural Network Compression Mechanism

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 […]

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Spatio-Temporal Crop Classification On Volumetric Data

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 […]

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Comprehensive Online Network Pruning via Learnable Scaling Factors

Comprehensive Online Network Pruning via Learnable Scaling Factors

Muhammad Umair Haider and Murtaza Taj Abstract: One of the major challenges in deploying deep neural network architectures is their size which has an adverse effect on their inference time and memory requirements. Deep CNNs can either be pruned width-wise by removing filters or depth-wise by removing layers and blocks. Width wise pruning (filter pruning) […]

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Kiln-Net

Kiln-Net

Usman Nazir, Usman Khalid Mian, Muhammad Usman Sohail, Murtaza Taj and Momin Uppal Abstract: The availability of high-resolution satellite imagery has enabled several new applications. One such application is identification of brick kilns for the elimination of modern day slavery which is also one of UN’s Sustainable Development Goals (SDG). This requires automated analysis of […]

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