Accuracy: 78.79GFLOPs: 2.335MParams: 14.811
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Network Pruning
Network Pruning is a popular approach to reduce a heavy network to obtain a light-weight form by removing redundancy in the heavy network. In this approach, a complex over-parameterized network is first trained, then pruned based on come criterions, and finally fine-tuned to achieve comparable performance with reduced parameters.
<span class="description-source">Source: Ensemble Knowledge Distillation for Learning Improved and Efficient Networks </span>
개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.
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Dataset기록된 모델 예시MetricPaperCode
데이터셋
5개논문
Top-1 Accuracy: 74.31
Top-1 Accuracy: 75.64
Top-1 Accuracy: 76.03
Top-1 Accuracy: 74
Top-1 Accuracy: 74.68
Top-1 Accuracy: 76.93
Accuracy: 78.0GFLOPs: 2.5
Top-1 Accuracy: 76.17
Top-1 Accuracy: 75.5
라이브러리
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