activity
20152021
most citedA Data and Model-Parallel, Distributed and Scalable Framework for Training of Deep Networks in Apache Spark

9 citations · 21 across the 8 of their papers we have counts for

collaborators

12 papers

cs.CV2021

Deriving Explanation of Deep Visual Saliency Models

Sai Phani Kumar Malladi, Jayanta Mukhopadhyay, Chaker Larabi +1

Deep neural networks have shown their profound impact on achieving human level performance in visual saliency prediction. However, it is still unclear how they learn the task and w…

cs.CV20211 cited

Understanding Character Recognition using Visual Explanations Derived from the Human Visual System and Deep Networks

Chetan Ralekar, Shubham Choudhary, Tapan Kumar Gandhi +1

Human observers engage in selective information uptake when classifying visual patterns. The same is true of deep neural networks, which currently constitute the best performing ar…

eess.IV20202 cited

Multi-Task Driven Explainable Diagnosis of COVID-19 using Chest X-ray Images

Aakarsh Malhotra, Surbhi Mittal, Puspita Majumdar +7

With increasing number of COVID-19 cases globally, all the countries are ramping up the testing numbers. While the RT-PCR kits are available in sufficient quantity in several count…

cs.CV2020

Compressive sensing based privacy for fall detection

Ronak Gupta, Prashant Anand, Santanu Chaudhury +2

Fall detection holds immense importance in the field of healthcare, where timely detection allows for instant medical assistance. In this context, we propose a 3D ConvNet architect…

cs.CV20197 cited

DSAL-GAN: Denoising based Saliency Prediction with Generative Adversarial Networks

Prerana Mukherjee, Manoj Sharma, Megh Makwana +5

Synthesizing high quality saliency maps from noisy images is a challenging problem in computer vision and has many practical applications. Samples generated by existing techniques…

cs.CV2018

Mode matching in GANs through latent space learning and inversion

Deepak Mishra, Prathosh A. P., Aravind Jayendran +2

Generative adversarial networks (GANs) have shown remarkable success in generation of unstructured data, such as, natural images. However, discovery and separation of modes in the…