An In-Memory-Computing Binary Neural Network Architecture With In-Memory Batch Normalization
This paper describes an in-memory computing architecture that combines full-precision computation for the first and last layers of a neural network while employing binary weights and input activations for the intermediate layers. This unique approach presents an efficient and effective solution for...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10639963/ |
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