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《深度学习与计算机视觉》配套代码

Home Page: https://frombeijingwithlove.github.io/dlcv_for_beginners/

License: BSD 3-Clause "New" or "Revised" License

Python 99.22% Shell 0.78%

dlcv_for_beginners's Introduction

《深度学习与计算机视觉》配套代码

封面

原名《深度学习与计算机视觉：实例入门》，请注意：这本书定位是入门书。

代码点这里。所有彩色图表电子版下载点这里，第五章和第六章的彩色图表参见在线版：第五章上，第五章下，第六章。

因为某些我无法理解的原因，书中英文被出版社要求强行翻译，最后：1）部分英文不同程度的被翻译成了中文，2）导致英文文献占大部分的文献列表未能放到书中。引用文献列表点这里。

内容错误请到这里提出。勘误表点这里。

购买链接：京东，亚马逊，当当

代码快速指引

第五章：numpy、matplotlib可视化的例子
第六章：物体检测标注小工具和本地数据增强小工具
第七章：二维平面分类，分别基于Caffe和MXNet
第八章：MNIST分类，分别基于Caffe和MXNet
第九章：基于Caffe回归图像混乱程度，及卷积核可视化
第十章：从ImageNet预训练模型进行迁移学习美食分类模型，混淆矩阵，ROC曲线绘制及模型类别响应图可视化，基于Caffe
第十二章：用MNIST训练Siamese网络，t-SNE可视化，基于Caffe
书中未包含杂七杂八：包括制造对抗样本(Caffe)、二维GAN及训练过程可视化(PyTorch)、给色情图片自动打马赛克(Caffe)、模型融合(Caffe)、图像分割(PyTorch)

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