Rethinking the Inception Architecture for Computer Vision 论文笔记
0 摘要 自从2014之后，深度卷积网络成为了计算机视觉解决方案的主流。模型的大小和计算成本的增加可以直接转换成质量收益。但是对于像移动视觉和大数据场景，计算效率和低参数计算仍是限制因素。本论文探索一种扩大网络的方法，目标是通过适当的分解卷积和积极的正则化来尽可能地有效利用增加的计算。 1 介绍 从2014年开始，通过利用更深更宽的网络，网络架构的质量得到了明显改善。VGGNet和GoogLeNe
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相关文章
- 1. Rethinking the Inception Architecture for Computer Vision
- 2. Inception V3 -- 《Rethinking the Inception Architecture for Computer Vision》论文笔记
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