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Publication Type : Conference Proceedings
Publisher : Smart Secure Systems – IoT and Analytics Perspective, Springer Singapore
Source : Smart Secure Systems – IoT and Analytics Perspective, Springer Singapore, Singapore (2017)
ISBN : 9789811076350
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Engineering
Department : Communication, Computer Science
Year : 2017
Abstract : In recent trends, computer vision applications have seen massive implementation of supervised learning with convolutional neural networks. In this paper, we have analyzed image classifiers and their classification accuracy. Also, we have measured their robustness upon introduction to various noise layers. Furthermore, we have implemented a generative adversarial network for the generator task of adversarial noise generation and the discriminator task of single image classification on the handwritten digits database. Our experiments are yielding progressive results and we have performed conditional and quantifiable evaluation of the generated samples.
Cite this Research Publication : A. Amit, Rishabh Saxena, and Dr. Don S., “Understanding How Adversarial Noise Affects Single Image Classification”, Smart Secure Systems – IoT and Analytics Perspective. Springer Singapore, Singapore, 2017.