RandWireNN: Exploring Randomly Wired Neural Networks for Image Recognition

时间 2020-12-30

标签 RandWireNN 繁體版

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在该研究中，来自 FAIR 的研究人员谢赛宁、Alexander Kirillov 、Ross Girshick 与何恺明通过随机神经网络连接的方式探索了比此前神经架构搜索更为广泛的连接形式，并实现了很好的效果。RandWireNN Abstract 用于图像识别的神经网络经过广泛的手工设计，从简单的链状模型发展到具有多条路径的结构。ResNets[11]和DenseNets[16]的成功在很大程

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1. 读Exploring Randomly Wired Neural Networks for Image Recognition
2. Exploring Self-attention for Image Recognition稿
3. CVPR2020《Exploring Self-attention for Image Recognition》
4. 【One Shot】《Siamese Neural Networks for One-shot Image Recognition》
5. 《Siamese Neural Networks for One-shot Image Recognition》笔记
6. CS231n Convolutional Neural Networks for Visual Recognition
7. Convolutional Neural Networks for Visual Recognition
8. 【论文笔记】Exploring Self-attention for Image Recognition
9. Convolutional Neural Networks for Speech Recognition///2014
10. Domain Adaptive Neural Networks for Object Recognition

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