第一种形式的数据增强包括生成图像平移和水平反射。我们通过从256×256图像中随机提取224×224块(及其水平反射)并在这些提取的块上训练我们的网络来做到这一点。这将我们训练集的大小增加了2048倍,尽管由此产生的训练示例当然是高度相互依赖的。如果没有这种方案,我们的网络会遭受严重的过拟合,这将迫使我们使用小得多...
论文地址:http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf 2012年,Alex Krizhevsky发表了AlexNet,它是LeNet的一种更深更宽的版本,网络扩大(5个卷积层+3个全连接层+1个softmax层)并以显著的优势赢得了困难的ImageNet竞赛。 AlexNet 将LeNet的思想扩展到更...
dl经典翻译中英对照alexnet imagenet classification with deep convolutional neural networks.pdf,ImageNet Classification with Deep Convolutional Neural Networks Alex Krizhevsky University of Toronto kriz@cs.utoronto.ca Ilya Sutskever University of Toronto i
Deep Convolutional Neural Networks (DeepCNN) refer to a variant of Artificial Neural Networks (ANN) that excel in image recognition tasks. They consist of multiple layers, including deep layers, which significantly contribute to the network's performance in contrast to other parameters like window si...
(Alexnet)ImageNet Classification with Deep Convolutional Neural Networks [原论文链接地址](https://proceedings.neurips.cc/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf) 摘要: 训练了一个大型的深度卷积神经网络,将ImageNet LSVRC-2010竞赛中的120万张高分辨率图像分为1000个不同的类别。该...
论文泛读 | ImageNet Classification with Deep Convolutional Neural Networks 论文链接:https://papers.nips.cc/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf Q1:解决了什么? 目前主要利用机器学习来解决目标识别任务; 机器学习可以通过“扩充数据集”、“强化训练模型”、“充实预防过拟合的手段...
曹旭东 A practical theory for designing very deep convolutional neural networks外文电子书籍.pdf,A practical theory for designing very deep convolutional neural networks Xudong Cao All models are wrong, some are useful -- George E. P. Box There is nothing
2 The Dataset 3 The Architecture 3.1 ReLU:f(x) = max(0, x) 在深度卷积神经网络中ReLU比tanh训练时间更快 Figure 1: A four-layer convolutional neural network with ReLUs (solid line) reaches a 25% training error rate on CIFAR-10 six times faster than an equivalent network with tanh neurons...
Convolutional neural networks ConvNets are designed to process data that come in the form of multiple arrays, for example a colour image composed of three 2D arrays containing pixel intensities in the three colour channels. Many data modalities are in the form of multiple arrays: 1D for signals...
Deep Convolutional Neural Networks 神经网络我们比较熟悉,但是当时主流的神经网络是SVM,树等等,deep convolution是一个新颖的概念。 二、摘要 Abstract 大概内容:我们训练了一个很大很深的神经网络,在ImageNet上对1000类进行分类。错误率比其他人都要低,网络中有6000万的参数,65000个神经元。网络结构中有5个卷积层,...