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
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
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,…
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…
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
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
Our joint research project with Iain Matthews at Disney Research Pittsburgh and Yaser Sheikh and Tomas Simon at Carnegie Mellon University is covered by Carnegie Mellon News. To quote from the press release: Computer graphic artists who produce computer-animated movies and games spend much time creating subtle movements such as expressions on faces, gesticulations on…
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…