郑重声明:原文参见标题,如有侵权,请联系作者,将会撤销发布! https://arxiv.org/abs/1312.6199v4 Abstract 深度神经网络是近年来在语音和视觉识别任务中取得最新性能的高度表达模型.虽然它们的表现力是它们成功的原因,但它也会使它们学习不可理解的解决方案,这些解决方案可能具有反直觉的特性.在本文中,我们介绍了两个这样的性质. 首先,根据不同的单元分析方法,我们发现单个高层单元和高层单元的随机线性组合之间没有区别.这表明,在神经网络的高层中,包含语义信息的是空间,…

On Explainability of Deep Neural Networks « Learning F# Functional Data Structures and Algorithms is Out!   On Explainability of Deep Neural Networks During a discussion yesterday with software architect extraordinaire David Lazar regarding how every…

前言:好久不见了,最近一直瞎忙活,博客好久都没有更新了,表示道歉.希望大家在新的一年中工作顺利,学业进步,共勉! 今天我们介绍深度神经网络的缺点:无论模型有多深,无论是卷积还是RNN,都有的问题:以图像为例,我们人为的加一些东西,然后会急剧的降低网络的分类正确率.比如下图: 在生成对抗样本之后,分类器把alps 以高置信度把它识别成了狗,下面的一幅图,是把puffer 加上一些我们人类可能自己忽视的东西,但是对分类器来说,这个东西可能很重要,这样分类器就会去调节它,这就导致分类器以百分之百的置信…

CNN综述文章 的翻译 [2019 CVPR] A Survey of the Recent Architectures of Deep Convolutional Neural Networks 翻译 综述深度卷积神经网络架构:从基本组件到结构创新 目录 摘要    1.引言    2.CNN基本组件        2.1 卷积层        2.2 池化层        2.3 激活函数        2.4 批次归一化        2.5 Dropout        2.6 全连接层…

An intriguing failing of convolutional neural networks and the CoordConv solution NeurIPS 2018 2019-10-10 15:01:48 Paper: https://arxiv.org/pdf/1807.03247.pdf Official TensorFlow Code: https://github.com/uber-research/coordconv Unofficial PyTorch Cod…

Must Know Tips/Tricks in Deep Neural Networks (by Xiu-Shen Wei)   Deep Neural Networks, especially Convolutional Neural Networks (CNN), allows computational models that are composed of multiple processing layers to learn representations of data with…

http://lamda.nju.edu.cn/weixs/project/CNNTricks/CNNTricks.html Deep Neural Networks, especially Convolutional Neural Networks (CNN), allows computational models that are composed of multiple processing layers to learn representations of data with mul…

Understanding the Effective Receptive Field in Deep Convolutional Neural Networks 理解深度卷积神经网络中的有效感受野 Abstract摘要 We study characteristics of receptive fields of units in deep convolutional networks. The receptive field size is a crucial issue in many vis…

About this Course If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "s…

colah's blog Blog About Contact Neural Networks, Manifolds, and Topology Posted on April 6, 2014 topology, neural networks, deep learning, manifold hypothesis Recently, there’s been a great deal of excitement and interest in deep neural networks beca…