[Paper Reading Note]Aggregated Residual Transformations for Deep Neural Networks
Paper Reading Note URL: https://arxiv.org/pdf/1611.05431.pdf TL;DR 提出了一种新的backbone结构ResNeXt用于图像分类任务，该结构具有同质性，具有多个相同拓扑结构的branch，这种结构也引入了除width, depth之外的一种新的维度cardinality（基数），实验证明，增加基数能够提高分类准确性，同时，随着模型容
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相关文章
- 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
- 4. 论文阅读：Aggregated Residual Transformations for Deep Neural Networks（ResNeXt）
- 5. Paper Reading: Slimmable Neural Networks
- 6. #Paper Reading# EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 7. 【论文阅读】Aggregated Residual Transformations for Deep Neural Networks Saining（ResNext）
- 8. 论文笔记——Aggregated Residual Transformations for Deep Neural Networks(ResNeXt)
- 9. 《2017-Aggregated Residual Transformations for Deep Neural Networks》论文阅读
- 10. 《ResNeXt: Aggregated Residual Transformations for Deep Neural Networks》论文笔记