Teaching Where to See: Knowledge Distillation-Based Attentive Information Transfer in Vehicle Maker Classification
Deep neural networks (DNNs) have been applied to various fields and achieved high performances. However, they require significant computing resources because of their numerous parameters, even though some of those parameters are redundant and do not contribute to the DNN performance. Recently, to ad...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8746266/ |