Quantized convolutional neural networks: a hardware perspective

Quantized convolutional neural networks: a hardware perspective

With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with classic machine learning techniques. On the other hand, the rise of the Internet of Things (IoT) and...

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Bibliographic Details
Main Authors: Li Zhang, Olga Krestinskaya, Mohammed E. Fouda, Ahmed M. Eltawil, Khaled Nabil Salama
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Electronics
Subjects:
convolutional neural networks
quantization
hardware
in-memory computing (IMC)
FPGA
Online Access:https://www.frontiersin.org/articles/10.3389/felec.2025.1469802/full
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https://www.frontiersin.org/articles/10.3389/felec.2025.1469802/full

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