DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution,and Fully CRFs
基于深度卷积网络，空洞卷积和全连接CRFs的图像语义分割（Deeplabv2）学习总结 Abstract 本文主要强调了基于深度学习语义分割的三大贡献：1.atrous convolution（空洞卷积）能明确控制特征响应分辨率和在不增大参数运算量的情况下增大卷积感受野获得更多的上下文信息；2.atrous spatial pyramid pooling（空洞空间金字塔池化）探索了一种采用多采样率
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