1 code implementation • IEEE Sensors Letters 2021 • Aryaman Sinha, Soumya P. Dash, N. B. Puhan
In this work, a non-orthogonal multiple access (NOMA)-inspired defense method is proposed to mitigate the effect of adversarial attacks, which pose a major challenge towards deep neural networks (DNNs) in multimedia networks.
Ranked #1 on Adversarial Defense on ImageNet
no code implementations • 3 Apr 2020 • Kalyan S Dash, N. B. Puhan, G Panda
The sparse concept coding of low entropy Tetrolet representation is found to extract the important hidden information (concept) for superior pattern discrimination.
no code implementations • 26 Dec 2018 • Bappaditya Mandal, N. B. Puhan, Avijit Verma
Our work aims at developing an efficient deep CNN learning-based method for food recognition alleviating these limitations by using partially labeled training data on generative adversarial networks (GANs).
no code implementations • 4 Dec 2018 • S. S. Behera, Bappaditya Mandal, N. B. Puhan
Among many biometrics such as face, iris, fingerprint and others, periocular region has the advantages over other biometrics because it is non-intrusive and serves as a balance between iris or eye region (very stringent, small area) and the whole face region (very relaxed large area).
no code implementations • 27 Sep 2017 • Paritosh Pandey, Akella Deepthi, Bappaditya Mandal, N. B. Puhan
In this work we propose a methodology for an automatic food classification system which recognizes the contents of the meal from the images of the food.