DeepLearning.ai深度学习课程笔记
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  • Introduction
  • 第一门课 神经网络和深度学习(Neural-Networks-and-Deep-Learning)chevron-right
  • 第二门课 改善深层神经网络:超参数调试、 正 则 化 以 及 优 化 (Improving Deep Neural Networks:Hyperparameter tuning, Regulariza
    • 第二门课 改善深层神经网络:超参数调试、正则化以及优化(Improving Deep Neural Networks:Hyperparameter tuning, Regularization andchevron-right
  • 第三门课 结构化机器学习项目(Structuring Machine Learning Projects)
    • 第三门课 结构化机器学习项目(Structuring Machine Learning Projects)chevron-right
  • 第四门课 卷积神经网络(Convolutional Neural Networks)
    • 第四门课 卷积神经网络(Convolutional Neural Networks)chevron-right
      • 第一周 卷积神经网络(Foundations of Convolutional Neural Networks)chevron-right
      • 第二周 深度卷积网络:实例探究(Deep convolutional models: case studies)chevron-right
      • 第三周 目标检测(Object detection)chevron-right
        • 3.1 目标定位(Object localization)
        • 3.2 特征点检测(Landmark detection)
        • 3.3 目标检测(Object detection)
        • 3.4 卷积的滑动窗口实现(Convolutional implementation of sliding windows)
        • 3.5 Bounding Box预测(Bounding box predictions)
        • 3.6 交并比(Intersection over union)
        • 3.7 非极大值抑制(Non-max suppression)
        • 3.8 Anchor Boxes
        • 3.9 YOLO 算法(Putting it together: YOLO algorithm)
        • 3.10 候选区域(选修)(Region proposals (Optional))
        • Autonomous driving application - Car detection
        • yolo_utils.py
      • 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)chevron-right
  • 第五门课 序列模型(Sequence Models)
    • 第五门课 序列模型(Sequence Models)chevron-right
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  1. 第四门课 卷积神经网络(Convolutional Neural Networks)chevron-right
  2. 第四门课 卷积神经网络(Convolutional Neural Networks)

第三周 目标检测(Object detection)

3.1 目标定位(Object localization)chevron-right3.2 特征点检测(Landmark detection)chevron-right3.3 目标检测(Object detection)chevron-right3.4 卷积的滑动窗口实现(Convolutional implementation of sliding windows)chevron-right3.5 Bounding Box预测(Bounding box predictions)chevron-right3.6 交并比(Intersection over union)chevron-right3.7 非极大值抑制(Non-max suppression)chevron-right3.8 Anchor Boxeschevron-right3.9 YOLO 算法(Putting it together: YOLO algorithm)chevron-right3.10 候选区域(选修)(Region proposals (Optional))chevron-rightAutonomous driving application - Car detectionchevron-rightyolo_utils.pychevron-right
Previouskt_utils.pychevron-leftNext3.1 目标定位(Object localization)chevron-right

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