Boosting the Hardware-Efficiency of Cascade Support Vector Machines for Embedded Classification Applications
Sign Up to like & getrecommendations! Published in 2017 at "International Journal of Parallel Programming"
DOI: 10.1007/s10766-017-0514-1
Abstract: Support Vector Machines (SVMs) are considered as a state-of-the-art classification algorithm capable of high accuracy rates for a different range of applications. When arranged in a cascade structure, SVMs can efficiently handle problems where the… read more here.
Keywords: classification; support vector; hardware; vector machines ... See more keywords
RoHNAS: A Neural Architecture Search Framework With Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3214312
Abstract: Neural Architecture Search (NAS) algorithms aim at finding efficient Deep Neural Network (DNN) architectures for a given application under given system constraints. DNNs are computationally-complex as well as vulnerable to adversarial attacks. In order to… read more here.
Keywords: hardware; robustness hardware; hardware efficiency; adversarial robustness ... See more keywords