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Docker\u5b89\u88c5\u7684\u5148\u51b3\u6761\u4ef6 2.5.2 \u5b89\u88c5Docker Desktop 2.5.3 \u62c9\u53d6Docker\u955c\u50cf 2.5.4 \u5feb\u901f\u5165\u95e8Docker\u7ec8\u7aef\u7684\u4f7f\u7528 2.5.5 VS Code\u4f7f\u7528Docker\u7684\u5feb\u901f\u5165\u95e8 \u7b2c\u4e09\u7ae0 \u7f16\u7a0b\u8bed\u8a00\u5feb\u901f\u5165\u95e8 <\/strong>3.1 Python\u7684\u8d77\u6e90\u3001\u5386\u53f2\u548c\u5e94\u7528 3.1.1 Python\u7684\u8d77\u6e90 3.1.2 Python\u7684\u5386\u53f2 3.1.3 Python\u7684\u5e94\u7528\u573a\u666f 3.2 Python\u7684\u57fa\u7840\u77e5\u8bc6 3.2.1 \u6ce8\u91ca 3.2.2 \u516d\u5927\u6570\u636e\u7c7b\u578b 3.3 Python\u7684\u5224\u65ad\u4e0e\u5faa\u73af\u8bed\u53e5 3.3.1 \u6bd4\u8f83\u8fd0\u7b97\u7b26\u548c\u5173\u7cfb\u8fd0\u7b97\u7b26 3.3.2 \u5224\u65ad\u8bed\u53e5 3.3.3 \u5faa\u73af\u8bed\u53e5 3.4 Python\u4e2d\u7684\u51fd\u6570 3.4.1 \u51fd\u6570\u7684\u5b9a\u4e49 3.4.2 \u51fd\u6570\u4e2d\u7684\u53d8\u91cf 3.4.3 \u9ad8\u7ea7\u51fd\u6570\u7528\u6cd5 3.4.4 Python\u4e2d\u7684\u6587\u4ef6\u64cd\u4f5c\u51fd\u6570 3.5 Python\u4e2d\u7684\u9762\u5411\u5bf9\u8c61\u7f16\u7a0b 3.5.1 \u9762\u5411\u5bf9\u8c61\u7f16\u7a0b VS \u9762\u5411\u8fc7\u7a0b\u7f16\u7a0b 3.5.2 \u7c7b\u4e0e\u5bf9\u8c61 3.5.3 \u9b54\u6cd5\u65b9\u6cd5 3.5.4 \u7c7b\u5c5e\u6027\u548c\u7c7b\u65b9\u6cd5 3.5.5 \u7ee7\u627f 3.5.6 \u591a\u6001 3.5.7 \u6a21\u5757\u7684\u4ecb\u7ecd\u548c\u5236\u4f5c 3.5.8 Python\u4e2d\u7684\u5305\u548c\u5e93 3.5.9 Python\u7684pip\u547d\u4ee4 3.6 PyTorch\u7684\u57fa\u7840\u77e5\u8bc6 3.6.1 PyTorch\u7684\u57fa\u672c\u6570\u636e\u7c7b\u578b 3.6.2 \u5f20\u91cf\u7684\u7d22\u5f15\uff0c\u5207\u7247\u4e0e\u7ef4\u5ea6\u53d8\u6362 3.6.3 \u5f20\u91cf\u7684\u62fc\u63a5\uff0c\u62c6\u5206\u4e0e\u7edf\u8ba1 \u7b2c\u56db\u7ae0 \u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7406\u8bba\u57fa\u7840 <\/strong>4.1\u5168\u8fde\u63a5\u795e\u7ecf\u7f51\u7edc 4.1.1\u7ebf\u6027\u6a21\u578b 4.1.2 \u56de\u5f52\u4e0e\u5206\u7c7b 4.1.3 \u611f\u77e5\u673a\u6a21\u578b 4.1.4 \u6fc0\u6d3b\u51fd\u6570 4.1.5 \u7ef4\u5ea6\u8bc5\u5492 4.1.6 \u8fc7\u62df\u5408\u4e0e\u6b20\u62df\u5408 4.1.7\u6b63\u5219 4.1.8\u6570\u636e\u589e\u5f3a 4.1.9\u6570\u503c\u4e0d\u7a33\u5b9a\u6027 4.2 \u57fa\u4e8e\u68af\u5ea6\u4e0b\u964d\u7684\u4f18\u5316\u7b97\u6cd5 4.2.1 \u4f18\u5316\u7b97\u6cd5\u7684\u6570\u5b66\u57fa\u7840 4.2.2 \u4f18\u5316\u5668 4.3 \u5377\u79ef\u795e\u7ecf\u7f51\u7edc 4.3.1 \u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7684\u8ba1\u7b97 4.3.2\u5377\u79ef\u7684\u8bbe\u8ba1\u601d\u60f3 4.3.3\u5377\u79ef\u5bf9\u56fe\u50cf\u7684\u7279\u5f81\u63d0\u53d6\u8fc7\u7a0b 4.3.4\u5377\u79ef\u6a21\u578b\u5b9e\u73b0\u56fe\u50cf\u8bc6\u522b 4.3.5\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7684\u5c42\u7ea7\u7ed3\u6784\u548c\u611f\u53d7\u91ce 4.3.6\u7b2c\u4e00\u4e2a\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\uff1aLeNet \u7b2c\u4e94\u7ae0 \u90a3\u4e9b\u5e74\u6211\u4eec\u8ffd\u8fc7\u7684ImageNet\u56fe\u50cf\u8bc6\u522b\u5927\u8d5b<\/strong> 5.1 ImageNet 5.1.1 \u4ec0\u4e48\u662fImageNet\uff1f 5.1.2 ImageNet\u6570\u636e\u96c6 5.1.3 ImageNet\u56fe\u50cf\u5206\u7c7b\u5927\u8d5b 5.2 AlexNet\uff1a\u62c9\u5f00\u6df1\u5ea6\u5b66\u4e60\u5e8f\u5e55 5.2.1 AlexNet\u7406\u8bba 5.2.2 AlexNet\u4ee3\u7801 5.2.3 AlexNet\u5c0f\u7ed3 5.3 ZFNet\uff1a\u5f00\u521b\u5377\u79ef\u6a21\u578b\u7684\u53ef\u89e3\u91ca\u6027 5.3.1 ZFNet\u7b80\u4ecb 5.3.2 \u5bf9\u5377\u79ef\u8ba1\u7b97\u7ed3\u679c\u7684\u53ef\u89c6\u5316 5.3.3 \u7f51\u7edc\u4e2d\u5bf9\u4e0d\u540c\u7279\u5f81\u7684\u5b66\u4e60\u901f\u5ea6 5.3.4 \u56fe\u7247\u5e73\u79fb\uff0c\u7f29\u653e\uff0c\u65cb\u8f6c\u5bf9CNN\u7684\u5f71\u54cd 5.3.5 ZFNet\u7684\u6539\u8fdb\u70b9 5.3.6 \u906e\u6321\u5bf9\u5377\u79ef\u6a21\u578b\u7684\u5f71\u54cd 5.3.7 ZFNet\u7684\u8c03\u53c2\u5b9e\u9a8c 5.3.8 ZFNet\u7684\u6a21\u578b\u4ee3\u7801\u5b9e\u73b0 5.3.9 ZFNet\u5c0f\u7ed3 5.4 VGGNet: \u63a2\u7d22\u6df1\u5ea6\u7684\u529b\u91cf 5.4.1 VGGNet\u6a21\u578b\u603b\u89c8 5.4.2 \u7f51\u7edc\u8d21\u732e\u603b\u7ed3 5.4.3 VGGNet\u7684\u6a21\u578b\u4ee3\u7801\u5b9e\u73b0 5.4.4 VGGNet\u6a21\u578b\u5c0f\u7ed3 5.5 GoogLeNet\uff1a\u63a2\u7d22\u5bbd\u5ea6\u7684\u529b\u91cf 5.5.1 GoogLeNetV1 5.5.2 GoogLeNetV2 5.5.3 GoogLeNetV3 5.5.4 GoogLeNetV4 5.5.5 GoogLeNetV5 5.6 ResNet\uff1a\u795e\u6765\u4e4b\u201c\u8def\u201d 5.6.1 \u6df1\u5ea6\u5b66\u4e60\u7f51\u7edc\u9000\u5316\u95ee\u9898 5.6.2\u6b8b\u5dee\u8fde\u63a5 5.6.3 ResNet\u6a21\u578b\u7684\u7f51\u7edc\u7ed3\u6784 5.6.4 \u6b8b\u5dee\u7684\u8c03\u53c2 5.6.5 \u6b8b\u5dee\u8fde\u63a5\u7684\u6e0a\u6e90 5.6.6 \u6b8b\u5dee\u8fde\u63a5\u6709\u6548\u6027\u7684\u89e3\u91ca 5.6.7 ResNet\u7684\u53d8\u4f53 5.6.8 ResNeXt 5.7 DenseNet\uff1a\u7279\u5f81\u590d\u7528\u771f\u9999 5.7.1 \u6a21\u578b\u8bbe\u8ba1\u52a8\u673a 5.7.2 DenseNet\u6a21\u578b\u7ed3\u6784 5.7.3 DenseNet\u6a21\u578b\u6bd4\u8f83 5.8 SENet\uff1a\u901a\u9053\u7ef4\u5ea6\u7684\u6ce8\u610f\u529b\u673a\u5236 5.8.1 SENet\u6a21\u578b\u603b\u89c8 5.8.2 SE\u6a21\u5757 5.8.3 SENet\u6548\u679c 5.8.4 SENet\u6a21\u578b\u5c0f\u7ed3 \u7b2c\u516d\u7ae0 \u6613\u4e8e\u5e94\u7528\u90e8\u7f72\u7684\u8f7b\u91cf\u5377\u79ef\u6a21\u578b<\/strong> 6.1 MobileNet V1 6.1.1 \u6a21\u578b\u8bbe\u8ba1\u52a8\u673a 6.1.2\u6df1\u5ea6\u53ef\u5206\u79bb\u5377\u79ef 6.1.3 MBConv\u6a21\u5757 6.1.4 MobileNet V1\u7f51\u7edc\u7ed3\u6784 6.1.5 MobileNet V1\u6a21\u578b\u5c0f\u7ed3 6.2 MobileNet V2 6.2.1 \u9006\u6b8b\u5dee\u7ed3\u6784 6.2.2 \u7ebf\u6027\u74f6\u9888\u7ed3\u6784 6.2.3 MobileNet V2\u7f51\u7edc\u7ed3\u6784 6.2.4 MobileNet V2\u6a21\u578b\u5c0f\u7ed3 6.3 MobileNet V3 6.3.1\u4f18\u5316\u7f51\u7edc\u6df1\u5c42\u7ed3\u6784 6.3.2 h-swish\u6fc0\u6d3b\u51fd\u6570 6.3.3 Squeeze-and-Excite 6.3.4 MobileNet V3\u6a21\u578b\u7ed3\u6784 6.3.5 MobileNet V3\u5c0f\u7ed3 6.4 ShuffleNet V1 6.4.1 \u7ec4\u5377\u79ef 6.4.2 \u901a\u9053\u6253\u6563\u64cd\u4f5c 6.4.3 ShuffleNet\u6a21\u5757 6.4.4 ShuffleNet V1\u6a21\u578b\u7ed3\u6784 6.4.5 ShuffleNet V1\u5c0f\u7ed3 6.5 ShuffleNet V2 6.5.1 ShuffleNet V2\u6a21\u578b\u8bbe\u8ba1\u52a8\u673a 6.5.2 \u8f7b\u91cf\u7ea7\u7f51\u7edc\u8bbe\u8ba1\u76845\u4e2a\u7ecf\u9a8c\u603b\u7ed3 6.5.3 ShuffleNet V2\u6a21\u578b\u7ed3\u6784 6.5.4 ShuffleNet V2\u5c0f\u7ed3 6.6 EfficientNet V1 6.6.1 EfficientNet V1\u6a21\u578b\u8bbe\u8ba1\u52a8\u673a 6.6.2 \u6a21\u578b\u7684\u4e09\u79cd\u7f29\u653e\u65b9\u6cd5 6.6.3 EfficientNet V1\u6a21\u578b\u7684\u7f29\u653e\u6bd4\u7387 6.6.4 EfficientNet V1\u6a21\u578b\u7ed3\u6784 6.6.5 EifficientNet V1\u5c0f\u7ed3 6.7 EifficentNet V2 6.7.1 EifficentNet V2\u6a21\u578b\u8bbe\u8ba1\u52a8\u673a 6.7.2 EifficentNet\u7684\u95ee\u9898 6.7.3 EfficientNet V2\u7684\u6539\u8fdb 6.7.4 EifficentNet V2\u5c0f\u7ed3 6.8 RepVGG 6.8.1 RepVGG\u6a21\u578b\u8bbe\u8ba1\u52a8\u673a 6.8.2 RepVGG\u6a21\u578b\u67b6\u6784 6.8.3 RepVGG\u91cd\u53c2\u6570\u5316 6.8.3 RepVGG\u5c0f\u7ed3 \u7b2c\u4e03\u7ae0 Transformer\u7684\u5f3a\u52bf\u5165\u4fb5 <\/strong>7.1 Transformer\u6a21\u578b 7.1.1 Transformer\u7b97\u6cd5\u89e3\u8bfb 7.1.2 \u81ea\u6ce8\u610f\u529b\u5c42 7.1.3\u591a\u5934\u81ea\u6ce8\u610f\u529b\u5c42 7.1.4 \u7f16\u7801\u5668\u7ed3\u6784 7.1.5 \u89e3\u7801\u5668\u7ed3\u6784 7.1.6 \u7ebf\u6027\u9876\u5c42\u548cSoftmax\u5c42 7.1.7 \u8f93\u5165\u6570\u636e\u7684\u5411\u91cf\u5316 7.1.8 Transformer\u5c0f\u7ed3 7.2 Vision Transformer\u6a21\u578b 7.2.1 ViT\u6846\u67b6 7.2.2 \u56fe\u7247\u6570\u636e\u7684\u5411\u91cf\u5316 7.2.3 VIT\u7684Transformer\u7f16\u7801\u5668 7.2.4 MLP Head\u6a21\u5757 7.2.5 \u6a21\u578b\u7f29\u653e 7.2.6 \u6df7\u5408ViT\u6a21\u578b 7.2.7 ViT\u5c0f\u7ed3 7.3 Swin Transformer 7.3.1 \u7f51\u7edc\u6574\u4f53\u6846\u67b6 7.3.2 Patch Merging\u8be6\u89e3 7.3.3 W-MSA\u8be6\u89e3 7.3.4 SW-MSA\u8be6\u89e3 7.3.5 \u76f8\u5bf9\u4f4d\u7f6e\u504f\u7f6e\u8be6\u89e3 7.3.6 Swin Transformer\u6a21\u578b\u8be6\u7ec6\u914d\u7f6e\u53c2\u6570 7.3.7 Swin Transformer\u6a21\u578b\u8ba8\u8bba\u4e0e\u603b\u7ed3 7.4 \u89c6\u89c9\u6ce8\u610f\u529b\u7f51\u7edc 7.4.1 \u76f8\u5173\u5de5\u4f5c 7.4.2 \u5927\u6838\u6ce8\u610f\u529b\u673a\u5236 7.4.3 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\u7b2c\u4e00\u7ae0 \u4eba\u5de5\u667a\u80fd\u4ecb\u7ecd<\/strong> 1.1\u4ec0\u4e48\u662f\u4eba\u5de5\u667a\u80fd 1.2\u4eba\u5de5\u667a\u80fd\u7684\u4e09\u6b21\u6d6a\u6f6e 1.2.1 \u4eba\u5de5\u667a\u80fd\u7684\u7b2c\u4e00\u6b21\u6d6a\u6f6e 1.2.2 \u4eba\u5de5\u667a\u80fd\u7684\u7b2c\u4e8c\u6b21\u6d6a\u6f6e 1.2.3 \u4eba\u5de5\u667a\u80fd\u7684\u7b2c\u4e09\u6b21\u6d6a\u6f6e 1.3\u4eba\u5de5\u667a\u80fd\u53d1\u5c55\u7684\u5fc5\u5907\u4e09\u8981\u7d20 1.3.1\u4eba\u5de5\u667a\u80fd\u53d1\u5c55\u7684\u57fa\u77f3\uff1a\u6570\u636e 1.3.2\u4eba\u5de5\u667a\u80fd\u53d1\u5c55\u7684\u52a8\u529b\uff1a\u7b97\u6cd5 1.3.3\u4eba\u5de5\u667a\u80fd\u53d1\u5c55\u7684\u624b\u6bb5\uff1a\u7b97\u529b 1.4\u4eba\u5de5\u667a\u80fd\u7684\u7f8e\u597d\u613f\u666f 1.4.1\u4e4c\u9e26\u4e0e\u9e66\u9e49\u7684\u542f\u793a 1.4.2\u4eba\u5de5\u667a\u80fd\u5230\u5e95\u6709\u591a\u667a\u80fd \u7b2c\u4e8c\u7ae0 \u6df1\u5ea6\u5b66\u4e60\u73af\u5883\u914d\u7f6e<\/strong> 2.1 \u4e13\u4e1a\u540d\u79f0\u548c\u914d\u7f6e\u65b9\u6848\u4ecb\u7ecd 2.1.1 \u4e13\u4e1a\u540d\u79f0\u4ecb\u7ecd 2.1.2 Window\u914d\u7f6ePyTorch\u6df1\u5ea6\u5b66\u4e60\u73af\u5883\u521d\u7ea7\u65b9\u6848 2.1.3 Window\u914d\u7f6ePyTorch\u6df1\u5ea6\u5b66\u73af\u5883\u8fdb\u9636\u65b9\u6848 2.2 Anaconda\u914d\u7f6ePython\u548cPyTorch 2.2.1 Anaconda\u7b80\u4ecb 2.2.2 Window\u7cfb\u7edf\u5b89\u88c5Anaconda 2.2.3 Linux\u7cfb\u7edf\u5b89\u88c5Anaconda 2.2.4 Anaconda\u7684\u5feb\u901f\u5165\u95e8 2.2.5 Anaconda\u914d\u7f6ePyTorch\u6df1\u5ea6\u5b66\u4e60\u73af\u5883 2.3 \u914d\u7f6eVS Code\u548cJupyter\u7684Python\u73af\u5883 2.3.1 VS Code\u4e0b\u8f7d\u4e0e\u5b89\u88c5 2.3.2 VS Code\u914d\u7f6ePython\u73af\u5883 2.3.3 Jupyter Notebook\u4e2d\u914d\u7f6ePython\u73af\u5883 2.4 \u914d\u7f6eWindows11\u548cLinux\u53cc\u7cfb\u7edf 2.4.1 Windows11\u914d\u7f6eWSL2\u7684\u8be6\u7ec6\u6b65\u9aa4 2.4.2 Windows11\u914d\u7f6eWSL2\u7684\u5e38\u89c1\u9519\u8bef 2.4.3 VS Code\u8fdc\u7a0b\u8fde\u63a5WSL2 2.5\u914d\u7f6eDocker\u6df1\u5ea6\u5b66\u4e60\u5f00\u53d1\u73af\u5883 2.5.1 Docker\u5b89\u88c5\u7684\u5148\u51b3\u6761\u4ef6 2.5.2 \u5b89\u88c5Docker Desktop 2.5.3 \u62c9\u53d6Docker\u955c\u50cf 2.5.4 \u5feb\u901f\u5165\u95e8Docker\u7ec8\u7aef\u7684\u4f7f\u7528 2.5.5 VS Code\u4f7f\u7528Docker\u7684\u5feb\u901f\u5165\u95e8 \u7b2c\u4e09\u7ae0 \u7f16\u7a0b\u8bed\u8a00\u5feb\u901f\u5165\u95e8 <\/strong>3.1 Python\u7684\u8d77\u6e90\u3001\u5386\u53f2\u548c\u5e94\u7528 3.1.1 Python\u7684\u8d77\u6e90 3.1.2 Python\u7684\u5386\u53f2 3.1.3 Python\u7684\u5e94\u7528\u573a\u666f 3.2 Python\u7684\u57fa\u7840\u77e5\u8bc6 3.2.1 \u6ce8\u91ca 3.2.2 \u516d\u5927\u6570\u636e\u7c7b\u578b 3.3 Python\u7684\u5224\u65ad\u4e0e\u5faa\u73af\u8bed\u53e5 3.3.1 \u6bd4\u8f83\u8fd0\u7b97\u7b26\u548c\u5173\u7cfb\u8fd0\u7b97\u7b26 3.3.2 \u5224\u65ad\u8bed\u53e5 3.3.3 \u5faa\u73af\u8bed\u53e5 3.4 Python\u4e2d\u7684\u51fd\u6570 3.4.1 \u51fd\u6570\u7684\u5b9a\u4e49 3.4.2 \u51fd\u6570\u4e2d\u7684\u53d8\u91cf 3.4.3 \u9ad8\u7ea7\u51fd\u6570\u7528\u6cd5 3.4.4 Python\u4e2d\u7684\u6587\u4ef6\u64cd\u4f5c\u51fd\u6570 3.5 Python\u4e2d\u7684\u9762\u5411\u5bf9\u8c61\u7f16\u7a0b 3.5.1 \u9762\u5411\u5bf9\u8c61\u7f16\u7a0b VS \u9762\u5411\u8fc7\u7a0b\u7f16\u7a0b 3.5.2 \u7c7b\u4e0e\u5bf9\u8c61 3.5.3 \u9b54\u6cd5\u65b9\u6cd5 3.5.4 \u7c7b\u5c5e\u6027\u548c\u7c7b\u65b9\u6cd5 3.5.5 \u7ee7\u627f 3.5.6 \u591a\u6001 3.5.7 \u6a21\u5757\u7684\u4ecb\u7ecd\u548c\u5236\u4f5c 3.5.8 Python\u4e2d\u7684\u5305\u548c\u5e93 3.5.9 Python\u7684pip\u547d\u4ee4 3.6 PyTorch\u7684\u57fa\u7840\u77e5\u8bc6 3.6.1 PyTorch\u7684\u57fa\u672c\u6570\u636e\u7c7b\u578b 3.6.2 \u5f20\u91cf\u7684\u7d22\u5f15\uff0c\u5207\u7247\u4e0e\u7ef4\u5ea6\u53d8\u6362 3.6.3 \u5f20\u91cf\u7684\u62fc\u63a5\uff0c\u62c6\u5206\u4e0e\u7edf\u8ba1 \u7b2c\u56db\u7ae0 \u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7406\u8bba\u57fa\u7840 <\/strong>4.1\u5168\u8fde\u63a5\u795e\u7ecf\u7f51\u7edc 4.1.1\u7ebf\u6027\u6a21\u578b 4.1.2 \u56de\u5f52\u4e0e\u5206\u7c7b 4.1.3 \u611f\u77e5\u673a\u6a21\u578b 4.1.4 \u6fc0\u6d3b\u51fd\u6570 4.1.5 \u7ef4\u5ea6\u8bc5\u5492 4.1.6 \u8fc7\u62df\u5408\u4e0e\u6b20\u62df\u5408 4.1.7\u6b63\u5219 4.1.8\u6570\u636e\u589e\u5f3a 4.1.9\u6570\u503c\u4e0d\u7a33\u5b9a\u6027 4.2 \u57fa\u4e8e\u68af\u5ea6\u4e0b\u964d\u7684\u4f18\u5316\u7b97\u6cd5 4.2.1 \u4f18\u5316\u7b97\u6cd5\u7684\u6570\u5b66\u57fa\u7840 4.2.2 \u4f18\u5316\u5668 4.3 \u5377\u79ef\u795e\u7ecf\u7f51\u7edc 4.3.1 \u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7684\u8ba1\u7b97 4.3.2\u5377\u79ef\u7684\u8bbe\u8ba1\u601d\u60f3 4.3.3\u5377\u79ef\u5bf9\u56fe\u50cf\u7684\u7279\u5f81\u63d0\u53d6\u8fc7\u7a0b 4.3.4\u5377\u79ef\u6a21\u578b\u5b9e\u73b0\u56fe\u50cf\u8bc6\u522b 4.3.5\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7684\u5c42\u7ea7\u7ed3\u6784\u548c\u611f\u53d7\u91ce 4.3.6\u7b2c\u4e00\u4e2a\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\uff1aLeNet \u7b2c\u4e94\u7ae0 \u90a3\u4e9b\u5e74\u6211\u4eec\u8ffd\u8fc7\u7684ImageNet\u56fe\u50cf\u8bc6\u522b\u5927\u8d5b<\/strong> 5.1 ImageNet 5.1.1 \u4ec0\u4e48\u662fImageNet\uff1f 5.1.2 ImageNet\u6570\u636e\u96c6 5.1.3 ImageNet\u56fe\u50cf\u5206\u7c7b\u5927\u8d5b 5.2 AlexNet\uff1a\u62c9\u5f00\u6df1\u5ea6\u5b66\u4e60\u5e8f\u5e55 5.2.1 AlexNet\u7406\u8bba 5.2.2 AlexNet\u4ee3\u7801 5.2.3 AlexNet\u5c0f\u7ed3 5.3 ZFNet\uff1a\u5f00\u521b\u5377\u79ef\u6a21\u578b\u7684\u53ef\u89e3\u91ca\u6027 5.3.1 ZFNet\u7b80\u4ecb 5.3.2 \u5bf9\u5377\u79ef\u8ba1\u7b97\u7ed3\u679c\u7684\u53ef\u89c6\u5316 5.3.3 \u7f51\u7edc\u4e2d\u5bf9\u4e0d\u540c\u7279\u5f81\u7684\u5b66\u4e60\u901f\u5ea6 5.3.4 \u56fe\u7247\u5e73\u79fb\uff0c\u7f29\u653e\uff0c\u65cb\u8f6c\u5bf9CNN\u7684\u5f71\u54cd 5.3.5 ZFNet\u7684\u6539\u8fdb\u70b9 5.3.6 \u906e\u6321\u5bf9\u5377\u79ef\u6a21\u578b\u7684\u5f71\u54cd 5.3.7 ZFNet\u7684\u8c03\u53c2\u5b9e\u9a8c 5.3.8 ZFNet\u7684\u6a21\u578b\u4ee3\u7801\u5b9e\u73b0 5.3.9 ZFNet\u5c0f\u7ed3 5.4 VGGNet: \u63a2\u7d22\u6df1\u5ea6\u7684\u529b\u91cf 5.4.1 VGGNet\u6a21\u578b\u603b\u89c8 5.4.2 \u7f51\u7edc\u8d21\u732e\u603b\u7ed3 5.4.3 VGGNet\u7684\u6a21\u578b\u4ee3\u7801\u5b9e\u73b0 5.4.4 VGGNet\u6a21\u578b\u5c0f\u7ed3 5.5 GoogLeNet\uff1a\u63a2\u7d22\u5bbd\u5ea6\u7684\u529b\u91cf 5.5.1 GoogLeNetV1 5.5.2 GoogLeNetV2 5.5.3 GoogLeNetV3 5.5.4 GoogLeNetV4 5.5.5 GoogLeNetV5 5.6 ResNet\uff1a\u795e\u6765\u4e4b\u201c\u8def\u201d 5.6.1 \u6df1\u5ea6\u5b66\u4e60\u7f51\u7edc\u9000\u5316\u95ee\u9898 5.6.2\u6b8b\u5dee\u8fde\u63a5 5.6.3 ResNet\u6a21\u578b\u7684\u7f51\u7edc\u7ed3\u6784 5.6.4 \u6b8b\u5dee\u7684\u8c03\u53c2 5.6.5 \u6b8b\u5dee\u8fde\u63a5\u7684\u6e0a\u6e90 5.6.6 \u6b8b\u5dee\u8fde\u63a5\u6709\u6548\u6027\u7684\u89e3\u91ca 5.6.7 ResNet\u7684\u53d8\u4f53 5.6.8 ResNeXt 5.7 DenseNet\uff1a\u7279\u5f81\u590d\u7528\u771f\u9999 5.7.1 \u6a21\u578b\u8bbe\u8ba1\u52a8\u673a 5.7.2 DenseNet\u6a21\u578b\u7ed3\u6784 5.7.3 DenseNet\u6a21\u578b\u6bd4\u8f83 5.8 SENet\uff1a\u901a\u9053\u7ef4\u5ea6\u7684\u6ce8\u610f\u529b\u673a\u5236 5.8.1 SENet\u6a21\u578b\u603b\u89c8 5.8.2 SE\u6a21\u5757 5.8.3 SENet\u6548\u679c 5.8.4 SENet\u6a21\u578b\u5c0f\u7ed3 \u7b2c\u516d\u7ae0 \u6613\u4e8e\u5e94\u7528\u90e8\u7f72\u7684\u8f7b\u91cf\u5377\u79ef\u6a21\u578b<\/strong> 6.1 MobileNet V1 6.1.1 \u6a21\u578b\u8bbe\u8ba1\u52a8\u673a 6.1.2\u6df1\u5ea6\u53ef\u5206\u79bb\u5377\u79ef 6.1.3 MBConv\u6a21\u5757 6.1.4 MobileNet V1\u7f51\u7edc\u7ed3\u6784 6.1.5 MobileNet V1\u6a21\u578b\u5c0f\u7ed3 6.2 MobileNet V2 6.2.1 \u9006\u6b8b\u5dee\u7ed3\u6784 6.2.2 \u7ebf\u6027\u74f6\u9888\u7ed3\u6784 6.2.3 MobileNet V2\u7f51\u7edc\u7ed3\u6784 6.2.4 MobileNet V2\u6a21\u578b\u5c0f\u7ed3 6.3 MobileNet V3 6.3.1\u4f18\u5316\u7f51\u7edc\u6df1\u5c42\u7ed3\u6784 6.3.2 h-swish\u6fc0\u6d3b\u51fd\u6570 6.3.3 Squeeze-and-Excite 6.3.4 MobileNet V3\u6a21\u578b\u7ed3\u6784 6.3.5 MobileNet V3\u5c0f\u7ed3 6.4 ShuffleNet V1 6.4.1 \u7ec4\u5377\u79ef 6.4.2 \u901a\u9053\u6253\u6563\u64cd\u4f5c 6.4.3 ShuffleNet\u6a21\u5757 6.4.4 ShuffleNet V1\u6a21\u578b\u7ed3\u6784 6.4.5 ShuffleNet V1\u5c0f\u7ed3 6.5 ShuffleNet V2 6.5.1 ShuffleNet 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