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
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
PhD (Stipend, Fees) 2 x PhD Position in Agriculture Robotics, Machine Learning, Computer Vision 2 x PhD Position in Satellite Imagery, Deep Learning, Image Processing MS (Stipend) 2 x MS Position in Agriculture Robotics, Machine Learning, Computer Vision 2 x MS Position in Satellite Imagery, Deep Learning, Image Processing How To Apply: Email: murtaza.taj@lums.edu.pk Apply Online: https://admissions.lums.edu.pk/
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 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…
Our NRPU proposal on “Analyzing and Forecasting Socio-economic development using Satellite Imagery of Districts of Punjab” has been approved for funding by HEC. Acceptance rate among CS & IT related proposals in NRPU call for 2017-18 was only 3% and the overall acceptance rate was only 28%. Our is among 1104 accepted proposals out of total…
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
Our paper titled “Stereoential Net: Deep Network for Learning Building Height Using Stereo Imagery” accepted at ICONIP 2023. This work was an outcome of PhD Thesis by Sana Jabbar More info: Click here