[Paper Reading Note]Aggregated Residual Transformations for Deep Neural Networks
Paper Reading Note URL: https://arxiv.org/pdf/1611.05431.pdf TL;DR 提出了一種新的backbone結構ResNeXt用於圖像分類任務，該結構具有同質性，具有多個相同拓撲結構的branch，這種結構也引入了除width, depth之外的一種新的維度cardinality（基數），實驗證明，增加基數能夠提高分類準確性，同時，隨着模型容
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相關文章
- 1. Aggregated Residual Transformations for Deep Neural Networks
- 2. ResNeXt - Aggregated Residual Transformations for Deep Neural Networks
- 3. CNN--ResNeXt--Aggregated Residual Transformations for Deep Neural Networks
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- 5. Paper Reading: Slimmable Neural Networks
- 6. #Paper Reading# EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 7. 【論文閱讀】Aggregated Residual Transformations for Deep Neural Networks Saining（ResNext）
- 8. 論文筆記——Aggregated Residual Transformations for Deep Neural Networks(ResNeXt)
- 9. 《2017-Aggregated Residual Transformations for Deep Neural Networks》論文閱讀
- 10. 《ResNeXt: Aggregated Residual Transformations for Deep Neural Networks》論文筆記