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Matteo Grimaldi, Valerio Tenace and Andrea Calimera
Convolutional Neural Networks (CNNs) are brain-inspired computational models designed to recognize patterns. Recent advances demonstrate that CNNs are able to achieve, and often exceed, human capabilities in many application domains. Made of several mill...
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Jeff Dix, Jeremy Holleman and Benjamin J. Blalock
A programmable, energy-efficient analog hardware implementation of a multilayer perceptron (MLP) is presented featuring a highly programmable system that offers the user the capability to create an MLP neural network hardware design within the available ...
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Duc-Minh Ngo, Dominic Lightbody, Andriy Temko, Cuong Pham-Quoc, Ngoc-Thinh Tran, Colin C. Murphy and Emanuel Popovici
This study proposes a heterogeneous hardware-based framework for network intrusion detection using lightweight artificial neural network models. With the increase in the volume of exchanged data, IoT networks? security has become a crucial issue. Anomaly...
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