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Accelerators for convolutional neural networks
- Munir, Arslan;
- Kong, Joonho;
- Qureshi, Mahmood Azhar
SCOPUS
2초록
Accelerators for Convolutional Neural Networks provides basic deep learning knowledge and instructive content to build up convolutional neural network (CNN) accelerators for the Internet of things (IoT) and edge computing practitioners, elucidating compressive coding for CNNs, presenting a two-step lossless input feature maps compression method, discussing arithmetic coding -based lossless weights compression method and the design of an associated decoding method, describing contemporary sparse CNNs that consider sparsity in both weights and activation maps, and discussing hardware/software co-design and co-scheduling techniques that can lead to better optimization and utilization of the available hardware resources for CNN acceleration. © 2024 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
- 제목
- Accelerators for convolutional neural networks
- 저자
- Munir, Arslan; Kong, Joonho; Qureshi, Mahmood Azhar
- 발행일
- 2023
- 유형
- Book
- 페이지
- 1 ~ 288
- 언어
- ENG
- 출판사
- wiley
- 분량
- 288 페이지