Hybrid Binary Neural Networks: A Tutorial Review

被引：1

作者：

Cetin, Ahmet Enis ^{[1
]}

Pan, Hongyi ^{[1
]}

机构：

[1] Univ Illinois, Dept Elect & Engn, Chicago, IL 60680 USA

来源：

2023 IEEE 41ST VLSI TEST SYMPOSIUM, VTS | 2023年

关键词：

Binary neurons; Binary Neural Networks; Walsh-Hadamard Transform; RECOGNITION;

D O I：

10.1109/VTS56346.2023.10139963

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this article, we review neural networks which have neurons with binary operations or networks that use binary transforms such as the Walsh-Hadamard transform (WHT). Neural networks with binary neurons or binary layers can be used in edge applications and/or applications requiring energy-efficient decision-making. WHT-based network is as accurate as the regular neural networks in the CIFAR-10 and the Tiny ImageNet image databases.

引用

页数：12

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