1. 为什么介绍此文? Triplet net 改进工作之一,主要思想是在大数据集(人脸识别)上的困难样本挖掘.人脸识别工作对于图像对匹配而言很有借鉴意义,共性是特征的提取和样本数据的挖掘. Tripnet net源于文章Deep metric learning using triplet network,在论文中也提出了用于训练三张图像的triplet loss.许多类似的人脸识别.匹配工作都是在大数据集上实现的,这就要求对数据的高效利用.原因是大多数样本在训练中后期不再有梯度贡献,例如含有m…

(一)Highway Networks 与 Deep Networks 的关系 理论实践表明神经网络的深度是至关重要的,深层神经网络在很多方面都已经取得了很好的效果,例如,在1000-class ImageNet数据集上的图像分类任务通过利用深层神经网络把准确率从84%提高到了95%,然而,在训练深层神经网络的时候却是非常困难的,神经网络的层数越多,存在的问题也就越多(例如大家熟知的梯度消失.梯度爆炸问题,下文会详细讲解).训练起来也就是愈加困难,这是一个公认的难题. 2015年由Rupesh…

this blog from: http://blog.demofox.org/2017/03/09/how-to-train-neural-networks-with-backpropagation/ How to Train Neural Networks With Backpropagation Posted on March 9 2017 by Demofox This post is an attempt to demystify backpropagation, which is t…

这里翻译下<Deep face recognition: a survey v4>. 1 引言 由于它的非侵入性和自然特征,人脸识别已经成为身份识别中重要的生物认证技术,也已经应用到许多领域,如军事,进入,公共安全和日常生活.FR自然在CVPR会议中也占据了十分长的时间.早在1990年代,随着特征脸的提出[157],FR就成为了一个比较热门的研究领域.过去基于特征进行FR的里程碑方法在图1中有所展示 如图1所示,其中介绍了4个主流技术的发展过程: holistic 方法:通过某种分布假设去直接…

Imagine you're an engineer who has been asked to design a computer from scratch. One day you're working away in your office, designing logical circuits, setting out AND gates, OR gates, and so on, when your boss walks in with bad news. The customer h…

About this Course This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applica…

When a golf player is first learning to play golf, they usually spend most of their time developing a basic swing. Only gradually do they develop other shots, learning to chip, draw and fade the ball, building on and modifying their basic swing. In a…

Classifying plankton with deep neural networks The National Data Science Bowl, a data science competition where the goal was to classify images of plankton, has just ended. I participated with six other members of my research lab, the Reservoir lab o…

(一)简述---承接上文---基于pytorch实现HighWay Networks之Train Deep Networks 上文已经介绍过Highway Netwotrks提出的目的就是解决深层神经网络训练困难的问题,以及简单的解释了为什么深层神经网络会出现梯度消失和梯度爆炸的问题,这里详细的介绍一些Highway Networks以及使用pytorch实现Highway Networks. (二)Highway Networks 什么是Highway Networks? Highway Ne…

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…