京东 11.11 红包
VGG05
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VGG 11
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VGG 07
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CNN: 4.4 triplet loss
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CNN: 4.4 triplet loss part 2
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VGG04
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2.07 Inception network
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plt.rcParams
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VGG 09
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2.05 network in network and 1x1 convolution
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AlexNet paper 07
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AlexNet paper 02
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2.03 残差网络 Residual network
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padding input images 函数
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吴恩达CNN1.9池化层pooling layer 笔记
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details of learning
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1.8 简单卷积网络示例 simple CNN
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吴恩达CNN1.4 Padding
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classic CNN models
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掰开揉碎CNN: pooling layer，strided convolution
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data augmentation
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2.06 谷歌inception网络介绍
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CNN: convolutional implementation of sliding window 02
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吴恩达CNN 1.2 Edge Detection Example 笔记
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VGG01
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1.6 卷积中'卷'的体现之处 Convolution over volumes
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VGG02
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CNN: convolutional sliding window implementation 01
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AlexNet paper 06
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EN 第二课作业解析：Regularization 01
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作业解读CNN3:YOLO non-max suppression
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tangent library
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1.1 计算机视觉：问题和难点
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CNN2.1 作业解读（无答案）
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CNN: 4.11 从2D到1D3D
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CNN: 4.5 face verification and binary classification
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np.pad
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对比pytorch, chainer (deep learning library) 更多关注
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作业解析CNN2.2: 如何搭建identity block
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Batch Normalization at test time
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(EN) 第二课作业解析：regularization 02