activity
20192021
most citedChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations

31 citations · 37 across the 4 of their papers we have counts for

collaborators

9 papers

cs.CE20211 cited

Improving Solar Cell Metallization Designs using Convolutional Neural Networks

Sumit Bhattacharya, Devanshu Arya, Debjani Bhowmick +2

Optimizing the design of solar cell metallizations is one of the ways to improve the performance of solar cells. Recently, it has been shown that Topology Optimization (TO) can be…

cs.CV202131 cited

ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations

Rishabh Tiwari, Udbhav Bamba, Arnav Chavan +1

Structured pruning methods are among the effective strategies for extracting small resource-efficient convolutional neural networks from their dense counterparts with minimal loss…

cs.CV2020

Rotation Equivariant Siamese Networks for Tracking

Deepak K. Gupta, Devanshu Arya, Efstratios Gavves

Rotation is among the long prevailing, yet still unresolved, hard challenges encountered in visual object tracking. The existing deep learning-based tracking algorithms use regular…

cs.CV20204 cited

Siamese Tracking with Lingual Object Constraints

Maximilian Filtenborg, Efstratios Gavves, Deepak Gupta

Classically, visual object tracking involves following a target object throughout a given video, and it provides us the motion trajectory of the object. However, for many practical…

cs.LG2020

HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphs

Devanshu Arya, Deepak K. Gupta, Stevan Rudinac +1

Graphs are the most ubiquitous form of structured data representation used in machine learning. They model, however, only pairwise relations between nodes and are not designed for…

cs.CV2020

Hard Occlusions in Visual Object Tracking

Thijs P. Kuipers, Devanshu Arya, Deepak K. Gupta

Visual object tracking is among the hardest problems in computer vision, as trackers have to deal with many challenging circumstances such as illumination changes, fast motion, occ…