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Weakly supervised object recognition with convolutional neural networks 论文解读
1. Model Overview1.1 什么是weakly supervised learninghttps://stackoverflow.com/questions/18944805/what-is-weakly-supervised-learning-bootstrappingIn short: In weakly supervised learning, you use a limited原创 2017-08-11 17:19:56 · 595 阅读 · 0 评论 -
Show and Tell Lessons learned from the 2015 MSCOCO Image Captioning Challenge论文及tensorflow源码解读
Show and Tell Lessons learned from the 2015 MSCOCO Image Captioning Challenge论文及tensorflow源码解读原创 2017-08-10 19:32:40 · 1740 阅读 · 1 评论 -
Inception v1 论文及源码
论文解读Network-in-networkR-CNNMultivation and High Level ConsiderationsArchitectural Details源码分析函数源码Going deeper with convolutions Christian Szegedy, Wei Liu, Yangqing Jia, Pierre...原创 2017-08-14 07:31:57 · 2862 阅读 · 3 评论 -
Show and Tell Lessons learned from the 2015 MSCOCO Image Captioning Challenge论文及tensorflow源码解读(2)
Source codebuild_modelbuild_image_embeddingsSource codebuild_modelbuild_image_embeddings在建立了图片和caption的输入后,这部分将图片转换为固定大小的tensor,就像论文提及的,使用已经用很大的数据集训练好的深度网络模型,不改变它的参数,直接用于特征提取。首先将图片丢入inception v3网络中,得原创 2017-08-12 22:03:22 · 775 阅读 · 0 评论 -
ImageNet Classification with Deep Convolutional Neural Networks -- 解读
论文解读先稍微翻译下数据集ImageNet 有各种分辨率的图片,我们需要固定大小的。所以,向下取样到 256 * 256。除此之外没有别的预处理。 ImageNet consists of variable-resolution images, while our system requires a constant input dimen- sionality. Therefore, we do原创 2017-08-14 18:32:30 · 731 阅读 · 0 评论