Paper accepted at ICONIP 2023
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
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Paper accepted at Journal of Medical Primatology
Our paper titled “An exploratory deep learning approach to investigate tuberculosis pathogenesis in nonhuman primate model: Combining automated radiological analysis with clinical and biomarkers data” accepted at Journal of Medical Primatology. This work was an outcome of work by Faisal Yaseen More info: Click here
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
CV Lab students win at Startup Weekend Lahore
Group Photo, a project at CV Lab by Aamer Zaheer, Ali Rehan, Abdur Rehman Naeem and Maria Zubair, won the first position at Startup Weekend Lahore. Group Photo android app solved the age-old problem that while taking a photograph of a group of friends, the photographer is missed out in the picture. The app, which…
PhD Proposal Defense: Usman Nazir
Learning Socio-economic Indicators from Remote Sensing Data Thursday 12 Sep, 2019 at 03:30 am in CS Smart Room 9-105 SBASSE. Abstract Progress on the UN Sustainable Development Goals (SDGs) is hampered by a persistent lack of data regarding key social, environmental, and economic indicators, particularly in developing countries. For example, data on poverty and slavery,…
Haris Baig to continue his Ph.D. studies at Dartmouth
M Haris Baig, who did his senior project in CV lab and also is a co-author on our ICCV 2011 paper, has received a fully funded PhD offer from Univ of Dartmouth, where he will be joining this Fall. He will be working with Lorenzo Torresani, who has pioneering work in the field of nonrigid…
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