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
Challenging the dogma of Relevance Feedback in Content based Image Retrieval Systems with Deep Learning May, 2018 at 3:00 pm in Smart Room 9-105 SBASSE. Abstract Association of images to their content based similar images in a database, is quite a fascinating challenge specially on social media platform where billions of tagged and untagged images…
Content Based Image Retrieval Using Hand Crafted Features Asim Waheed, Khawaja Umair Ul Hassan The project involved solving the Cross-View image matching problem between Satellite view images and Street view images. Many hand-crafted features were calculated, such as Histogram, HOG, Bag of Visual Words and VLAD using SIFT and SURF descriptors. The compiled features would…
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 “Spatio-Temporal driven Attention Graph Neural Network with Block Adjacency matrix (STAG-NN-BA) for Remote Land-use Change Detection” accepted at AAAI Fall 2023 Symposium on Artificial Intelligence and Climate: The Role of AI in a Climate-Smart Sustainable Future. This work was an outcome of MS Thesis work by Wadood Islam and PhD Thesis work…
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…
“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…