具体来说,我们在整个ImageNet训练集中对RGB像素值集进行PCA(主成分分析)。对于每个训练图像,我们添加找到的主成分的倍数,大小与相应的特征值成比例乘以从均值为零和标准差为0.1的高斯曲线中绘制的随机变量。因此,对于每个RGB图像像素Ixy=[IR xy, IG xy,IB xy]T,我们添加以下数量: 其中pi和λi分别是RGB像素值的3...
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...
[NIPS 2012 Hinton] ImageNet Classification with Deep Convolutional Neural Networks英文学习资料.pdf,ImageNet Classification with Deep Convolutional Neural Networks Alex Krizhevsky Ilya Sutskever Geoffrey Hinton University of Toronto Canada Paper with same
NIPS-2012-imagenet-classification-with-deep-convolutional-neural-networks-Paper.pdf 0x01 Abstract 训练一个deep convolutional nerual network来区分ImageNet的LSVRC-2010比赛中的120万张 high-resolution到1000个不同的class (网络效果)在我们的test中,我们错误率从37.5%到17%的提升,显著的好于现有的SOTA (网络结...
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...
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...
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,...
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...