ImageNet Classification with Deep Convolutional Neural Networks（翻译+总结）
网络架构 网络共有8层，五个卷积层和三个全连接层。接下来介绍一下网络架构的一些特点。 1.ReLU Nonlinearity 标准情况下神经元的输出一般采用tanh或者sigmoid作为激活函数，但是就梯度下降的训练时间而言，这些饱和非线性函数要比非饱和非线性函数f(x) = max(0, x)慢得多，这里将这种非线性单元称为Rectified Linear Units (ReLUs)。带有ReL
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相关文章
- 1. ImageNet Classification with Deep Convolutional Neural Networks （AlexNet）翻译
- 2. ImageNet Classification with Deep Convolutional Neural Networks
- 3. 《ImageNet Classification with Deep Convolutional Neural Network》
- 4. alexnet笔记（ImageNet Classification with Deep Convolutional Neural Networks）
- 5. 论文ImageNet Classification with Deep Convolutional Neural Networks（Alexnet2012）
- 6. AlexNet——ImageNet Classification with Deep Convolutional Neural Networks
- 7. AlexNet《ImageNet Classification with Deep Convolutional Neural Networks》
- 8. ImageNet Classification with Deep Convolutional Neural Networks -- 解读
- 9. ImageNet Classification with Deep Convolutional Neural Networks（Alexnet）
- 10. 【AlexNet】ImageNet Classification with Deep Convolutional Neural Networks