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
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 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 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 amongĀ 1104 accepted proposals out of total…
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…
Our paper titled “Stereollax Net: Stereo Parallax Based Deep Learning Network For Building Height Estimation” accepted at IEEE Transactions on Geoscience and Remote Sensing. This work was an outcome of PhD Thesis work by Sana Jabbar More info: Click here
“Using 3D Residual Network For Spatio-Temporal Analysis Of Remote Sensing Data”, “Adaptively Weighted Multi-Task Learning Using Inverse Validation Loss” and “Point Cloud Segmentation Using Hierarchical Tree for Architectural Models” have been accepted in “IEEE International Conference on Acoustic Speech and Signal Processing. This conference is going to be held from 12th to 17th May 2019…
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…