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.
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页数：12
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