ICLR2016_DELVING DEEPER INTO CONVOLUTIONAL NETWORKS Note here: Ballas recently proposed a novel framework on learning video representation, following is the review note after reading his paper. Link: http://arxiv.org/pdf/1511.06432v4.pdf [Brief intro…

Two-Stream Convolutional Networks for Action Recognition in Videos & Towards Good Practices for Very Deep Two-Stream ConvNets Note here: it's a learning note on the topic of video representations. This note incorporates two papers about popular two-s…

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition 2018-01-28  15:45:13  研究背景和动机: 行人动作识别(Human Action Recognition)主要从多个模态的角度来进行研究,即:appearance,depth,optical-flow,以及 body skeletons.这其中,动态的人类骨骼点 通常是最具有信息量的,且能够和其他模态进行互补.…

[论文标题]Predict and Constrain: Modeling Cardinality in Deep Structured Prediction   (35th-ICML,PMLR) [论文作者]Nataly Brukhim,Amir Globerson [论文链接]Paper (13-pages // Single column) [摘要] 许多机器学习问题需要多维标签的预测.这种结构化预测模型可以从标签之间的依赖关系建模中获益.最近,已有研究提出了几种结构预测的深度学习方法.在…

目录 0. 论文地址 1. 概述 2. 可视化结构 2.1 Unpooling 2.2 Rectification: 2.3 Filtering: 3. Feature Visualization 4. Feature Evolution during Training 5. Feature Invariance 6. ZF-Net 7. 实验 8. 简单的可视化工具 9. 参考链接 @ 0. 论文地址 http://arxiv.org/pdf/1311.2901.pdf 1. 概述   本文设…

作者:wuliytTaotao 出处:https://www.cnblogs.com/wuliytTaotao/ 本作品采用知识共享署名-非商业性使用-相同方式共享 4.0 国际许可协议进行许可,欢迎转载,但未经作者同意必须保留此段声明,且在文章页面明显位置给出原文连接.         原文地址: https://www.cnblogs.com/wuliytTaotao/p/9488045.html     -------------------------------------------…

本文翻译自 SATYA MALLICK 的  "Neural Networks : A 30,000 Feet View for Beginners" 原文链接: https://www.learnopencv.com/neural-networks-a-30000-feet-view-for-beginners/ 翻译:coneypo 在这篇文章中,我会向大家简要的介绍下 Neural Networks / 神经网络: 可以作为 Machine Learning / 机器学习 和 D…

1.理解特征值,特征向量 一个对角阵\(A\),用它做变换时,自然坐标系的坐标轴不会发生旋转变化,而只会发生伸缩,且伸缩的比例就是\(A\)中对角线对应的数值大小. 对于普通矩阵\(A\)来说,是不是也可以找到这样的向量,使得经\(A\)变换后,不改变方向而只伸缩?答案是可以的,这种向量就是\(A\)的特征向量,而对应的伸缩比例就是对应的特征值. 特征值会有复数是为什么? 首先要知道,虚数单位\(i\)对应的是旋转\(90^o\),那么,如果特征值是复数,则对应的特征向量经矩阵\(A\)变换后将…

Unsupervised Learning of Video Representations using LSTMs Note here: it's a learning notes on new LSTMs architecture used as an unsupervised learning way of video representations. (More unsupervised learning related topics, you can refer to: Learnin…

https://github.com/colipso/face_recognition https://medium.com/@ageitgey/machine-learning-is-fun-part-4-modern-face-recognition-with-deep-learning-c3cffc121d78 http://www.cnblogs.com/neo-T/p/6511273.html…