DoubleQExt: Hardware and Memory Efficient CNN Through Two Levels of Quantization

DoubleQExt: Hardware and Memory Efficient CNN Through Two Levels of Quantization

To fulfil the tight area and memory constraints in IoT applications, the design of efficient Convolutional Neural Network (CNN) hardware becomes crucial. Quantization of CNN is one of the promising approach that allows the compression of large CNN into a much smaller one, which is very suitable for...

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Bibliographic Details
Main Authors: Jin-Chuan See, Hui-Fuang Ng, Hung-Khoon Tan, Jing-Jing Chang, Wai-Kong Lee, Seong Oun Hwang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Convolutional neural network
quantization
Internet of Things
deep learning
field programmable gate array
Online Access:https://ieeexplore.ieee.org/document/9663269/

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