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Found 5 papers, 1 papers with code
NOMARO: Defending against Adversarial Attacks by NOMA-Inspired Reconstruction Operation
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
Sparse Concept Coded Tetrolet Transform for Unconstrained Odia Character Recognition
The sparse concept coding of low entropy Tetrolet representation is found to extract the important hidden information (concept) for superior pattern discrimination.
Deep Convolutional Generative Adversarial Network Based Food Recognition Using Partially Labeled Data
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).
Cross-spectral Periocular Recognition: A Survey
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).
FoodNet: Recognizing Foods Using Ensemble of Deep Networks
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.
