A deep convolutional neural network based on nested residue number system-Reference-Cited by-同舟云学术

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A deep convolutional neural network based on nested residue number system

Published:2015-09 Issue: Volume: Page:
ISSN:
Container-title:2015 25th International Conference on Field Programmable Logic and Applications (FPL)
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Author:

Nakahara Hiroki,Sasao Tsutomu

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7284611/7293744/07293933.pdf?arnumber=7293933

Cited by 38 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Peculiarities of Applying Partial Convolutions to the Computation of Reduced Numerical Convolutions;Applied Sciences;2024-07-22

2. An end-to-end RNS CNN Accelerator;2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS);2024-04-22

3. Optimal Moduli Searching for RNS-Based Devices;2023 International Conference on Electrical, Computer and Energy Technologies (ICECET);2023-11-16

4. A Generalized Residue Number System Design Approach for Ultralow-Power Arithmetic Circuits Based on Deterministic Bit-Streams;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-11

5. Improving Residue-Level Sparsity in RNS-based Neural Network Hardware Accelerators via Regularization;2023 IEEE 30th Symposium on Computer Arithmetic (ARITH);2023-09-04

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