论文ImageNet Classification with Deep Convolutional Neural Networks（Alexnet2012）
一、论文关键点 1.神经网络在有了算力更好的gpu与更大的数据集合（ILSVRC和imagenet）后会取得更好的效果。 2.网络超参数(人为设定的，非机器自学习到的参数，如batchsize,weight decay,learning rate,epoches)的设置，权重及偏置的初始化(卷积核初始化方式：均值为0方差为1的高斯分布；偏置初始化方式：2,4,5卷积层及全连接层初始化为1，剩余层初
相关文章
- 1. ImageNet Classification with Deep Convolutional Neural Networks
- 2. 读文献——《ImageNet classification with deep convolutional neural networks》
- 3. alexnet笔记（ImageNet Classification with Deep Convolutional Neural Networks）
- 4. AlexNet——ImageNet Classification with Deep Convolutional Neural Networks
- 5. AlexNet《ImageNet Classification with Deep Convolutional Neural Networks》
- 6. ImageNet Classification with Deep Convolutional Neural Networks -- 解读
- 7. ImageNet Classification with Deep Convolutional Neural Networks （AlexNet）翻译
- 8. ImageNet Classification with Deep Convolutional Neural Networks（Alexnet）
- 9. 【AlexNet】ImageNet Classification with Deep Convolutional Neural Networks
- 10. AlexNet--ImageNet Classification with Deep Convolutional Neural Networks
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相关文章
- 1. ImageNet Classification with Deep Convolutional Neural Networks
- 2. 读文献——《ImageNet classification with deep convolutional neural networks》
- 3. alexnet笔记（ImageNet Classification with Deep Convolutional Neural Networks）
- 4. AlexNet——ImageNet Classification with Deep Convolutional Neural Networks
- 5. AlexNet《ImageNet Classification with Deep Convolutional Neural Networks》
- 6. ImageNet Classification with Deep Convolutional Neural Networks -- 解读
- 7. ImageNet Classification with Deep Convolutional Neural Networks （AlexNet）翻译
- 8. ImageNet Classification with Deep Convolutional Neural Networks（Alexnet）
- 9. 【AlexNet】ImageNet Classification with Deep Convolutional Neural Networks
- 10. AlexNet--ImageNet Classification with Deep Convolutional Neural Networks