On Class-Incremental Learning for Fully Binarized Convolutional Neural Networks-Reference-Cited by-同舟云学术

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On Class-Incremental Learning for Fully Binarized Convolutional Neural Networks

Published:2024-05-19 Issue: Volume:29 Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Circuits and Systems (ISCAS)
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Author:

Basso-Bert Yanis¹,Guicquero William²,Molnos Anca¹,Lemaire Romain¹,Dupret Antoine²

Affiliation:

1. Univ. Grenoble Alpes,CEA, Leti,Grenoble,France,F-38000

2. Univ. Grenoble Alpes,CEA, List,Grenoble,France,F-38000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10557746/10557828/10558661.pdf?arnumber=10558661

Reference37 articles.

1. Bi-narized neural networks;Hubara;Advances in Neural Information Processing Systems (NIPS),2016

2. Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem

3. Synaptic metaplasticity in binarized neural networks

4. Incremental Learning Meets Reduced Precision Networks

5. Class-Incremental Learning: Survey and Performance Evaluation on Image Classification

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