> For the complete documentation index, see [llms.txt](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks.md).

# 第四门课 卷积神经网络（Convolutional Neural Networks）

- [第一周 卷积神经网络（Foundations of Convolutional Neural Networks）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks.md)
- [1.1 计算机视觉（Computer vision）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/11-ji-suan-ji-shi-jue-ff08-computer-vision.md)
- [1.2 边缘检测示例（Edge detection example）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/12-bian-yuan-jian-ce-shi-li-ff08-edge-detection-example.md)
- [1.3 更多边缘检测内容（More edge detection）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/13-geng-duo-bian-yuan-jian-ce-nei-rong-ff08-more-edge-detection.md)
- [1.4 Padding](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/14-padding.md)
- [1.5 卷积步长（Strided convolutions）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/15-juan-ji-bu-chang-ff08-strided-convolutions.md)
- [1.6 三维卷积（Convolutions over volumes）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/16-san-wei-juan-ji-ff08-convolutions-over-volumes.md)
- [1.7 单层卷积网络（One layer of a convolutional network）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/17-dan-ceng-juan-ji-wang-luo-ff08-one-layer-of-a-convolutional-network.md)
- [1.8 简单卷积网络示例（A simple convolution network example）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/18-jian-dan-juan-ji-wang-luo-shi-li-ff08-a-simple-convolution-network-example.md)
- [1.9 池化层（Pooling layers）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/19-chi-hua-ceng-ff08-pooling-layers.md)
- [1.10 卷积神经网络示例（Convolutional neural network example）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/110-juan-ji-shenjing-wang-luo-shi-li-ff08-convolutional-neural-network-example.md)
- [1.11 为什么使用卷积？（Why convolutions?）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/111-wei-shi-yao-shi-yong-juan-ji-ff1f-ff08-why-convolutions.md)
- [Convolution model Step by Step](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/convolution-model-step-by-step.md)
- [Convolutional Neural Networks: Application](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/convolutional-neural-networks-application.md)
- [cnn\_utils](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/foundations-of-convolutional-neural-networks/cnnutils.md)
- [第二周 深度卷积网络：实例探究（Deep convolutional models: case studies）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies.md)
- [2.1 经典网络（Classic networks）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/22-jing-dian-wang-luoff08-classic-networks.md)
- [2.2 残差网络（Residual Networks (ResNets)）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/23-can-cha-wang-luo-ff08-residual-networks-resnets.md)
- [2.3 残差网络为什么有用？（Why ResNets work?）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/24-can-cha-wang-luo-wei-shi-yao-you-yong-ff1f-ff08-why-resnets-work.md)
- [2.4 网络中的网络以及 1×1 卷积（Network in Network and 1×1 convolutions）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/25-wang-luo-zhong-de-wang-luo-yi-ji-1-1-juan-ji-ff08-network-in-network-and-1-1-convolutions.md)
- [2.5 谷歌 Inception 网络简介（Inception network motivation）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/26-gu-ge-inception-wang-luo-jianjie-ff08-inception-network-motivation.md)
- [2.6 Inception 网络（Inception network）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/27-inception-wang-luo-ff08-inception-network.md)
- [2.7 迁移学习（Transfer Learning）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/29-qian-yi-xue-xi-ff08-transfer-learning.md)
- [2.8 数据扩充（Data augmentation）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/210-shu-ju-kuo-chong-ff08-data-augmentation.md)
- [2.9 计算机视觉现状（The state of computer vision）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/211-ji-suan-ji-shi-jue-xian-zhuang-ff08-the-state-of-computer-vision.md)
- [Residual Networks](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/residual-networks.md)
- [Keras tutorial - the Happy House](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/keras-tutorial-happy-house-v2.md)
- [kt\_utils.py](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/deep-convolutional-models-case-studies/ktutils-py.md)
- [第三周 目标检测（Object detection）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection.md)
- [3.1 目标定位（Object localization）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/31-mu-biao-ding-wei-ff08-object-localization.md)
- [3.2 特征点检测（Landmark detection）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/32-te-zheng-dian-jian-ce-ff08-landmark-detection.md)
- [3.3 目标检测（Object detection）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/33-mu-biao-jian-ce-ff08-object-detection.md)
- [3.4 卷积的滑动窗口实现（Convolutional implementation of sliding windows）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/34-juan-ji-de-hua-dong-chuang-kou-shi-xian-ff08-convolutional-implementation-of-sliding-windows.md)
- [3.5 Bounding Box预测（Bounding box predictions）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/35-bounding-boxyu-ce-ff08-bounding-box-predictions.md)
- [3.6 交并比（Intersection over union）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/36-jiao-bing-bi-ff08-intersection-over-union.md)
- [3.7 非极大值抑制（Non-max suppression）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/37-fei-ji-da-zhi-yi-zhi-ff08-non-max-suppression.md)
- [3.8 Anchor Boxes](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/38-anchor-boxes.md)
- [3.9 YOLO 算法（Putting it together: YOLO algorithm）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/39-yolo-suan-fa-ff08-putting-it-together-yolo-algorithm.md)
- [3.10 候选区域（选修）（Region proposals (Optional)）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/310-hou-xuan-qu-yu-ff08-xuan-xiu-ff09-ff08-region-proposals-optional.md)
- [Autonomous driving application - Car detection](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/autonomous-driving-application-car-detection-v3.md)
- [yolo\_utils.py](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/object-detection/yoloutils-py.md)
- [第四周 特殊应用：人脸识别和神经风格转换（Special applications: Face recognition \&Neural style transfer）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications.md)
- [4.1 什么是人脸识别？（What is face recognition?）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/41-shi-yao-shi-ren-lian-shi-bie-ff1f-ff08-what-is-face-recognition.md)
- [4.2 One-Shot学习（One-shot learning）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/42-one-shotxue-xi-ff08-one-shot-learning.md)
- [4.3 Siamese 网络（Siamese network）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/43-siamese-wang-luo-ff08-siamese-network.md)
- [4.4 Triplet 损失（Triplet 损失）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/44-triplet-sun-shi-ff08-triplet-sun-shi-ff09.md)
- [4.5 面部验证与二分类（Face verification and binary classification）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/45-mian-bu-yan-zheng-yu-er-fen-lei-ff08-face-verification-and-binary-classification.md)
- [4.6 什么是深度卷积网络？（What are deep ConvNets learning?）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/47-shi-yao-shi-shen-du-juan-ji-wang-luo-ff1f-ff08-what-are-deep-convnets-learning.md)
- [4.7 代价函数（Cost function）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/48-dai-jia-han-shu-ff08-cost-function.md)
- [4.8 内容代价函数（Content cost function）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/49-nei-rong-dai-jia-han-shu-ff08-content-cost-function.md)
- [4.9 风格代价函数（Style cost function）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/410-feng-ge-dai-jia-han-shu-ff08-style-cost-function.md)
- [4.10 一维到三维推广（1D and 3D generalizations of models）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/411-yi-wei-dao-san-wei-tui-guang-ff08-1d-and3d-generalizations-of-models.md)
- [Art Generation with Neural Style Transfer](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/art-generation-with-neural-style-transfer-v2.md)
- [nst\_utils.py](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/nstutils-py.md)
- [Face Recognition for the Happy House](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/face+recognition+for+the+happy+house+-+v3.md)
- [fr\_utils.py](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/frutils-py.md)
- [inception\_blocks.py](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/inceptionblocks-py.md)