URL 收藏

1 Hyper-Textbook: Optimization Models and Applications  —  Fall 2014 

https://inst.eecs.berkeley.edu/~ee127a/book/login/index.html

二 openfabmap

https://code.google.com/p/openfabmap/

openFABMAP

This is an open and modifiable code-source which implements the Fast Appearance-based Mapping algorithm (FAB-MAP) originally developed by Mark Cummins and Paul Newman. OpenFABMAP was designed from published FAB-MAP theory and is for personal and research use.

FAB-MAP is a Simultaneous Localisation and Mapping algorithm which operates in appearance space only. FAB-MAP performs location matching between places that have been visited within the world as well as providing a measure of the probability of being at a new, previously unvisited location. Camera images form the sole input to the system, from which bag-of-words models are formed through the extraction of appearance-based (e.g. SURF) features.

The code has implementations of

• Feature Detection and Extraction and Bag-of-words models using OpenCV
• Chow-Liu tree implementation
• FAB-MAP v1.0 (Cummins & Newman 2008)
• FAB-MAP v1.0 using a Look-up-table for improved computation speed
• FAB-MAP with Fast-Bailout (Cummins & Newman 2010)
• FAB-MAP v2.0 (Cummins & Newman 2010)

For an overview of OpenFABMAP see (Glover et al. 2012). OpenFABMAP was first used in (Glover et al. 2010).

As of the latest version, openFABMAP is dependent solely on OpenCV 2.3 or higher. The project is designed to integrate with OpenCV2.3 2D feature-based methods and storage methods. The project has a CMake build environment for general use on both Linux and Windows systems. See the README file for more information on compiling the code.

OpenFABMAP is also designed to integrate with Robot Operating System (ROS). See the CyPhy-ROS page for a package that has implemented openFABMAP as a ROS node.

Check out the wiki (under construction) for some instructions and tips on running openFABMAP.

For questions on how to modify the source to your specific implementation, bug reporting, comments and suggestions, or if you would like to become involved in developing the openFABMAP project beyond the current implementation contact via the google group.

Citations Endnote BibTex

三

吴立德 《深度学习课程》

http://www.youku.com/playlist_show/id_21508721.html

四

1.  火光摇曳团队分享文档
     Docs
神奇的伽玛函数
LDA 数学八卦
正态分布的前世今生
   Paper
Towards Topic Modeling for Big Data
Peacock: Learning Long-Tail Topic Features for Industrial Applications，Yi Wang, Xuemin Zhao, Zhenlong Sun, Hao Yan, Lifeng Wang, Zhihui Jin, Liubin Wang, Yang Gao, Ching Law, Jia Zeng，ACM TIST 2014
    Slides
正态分布(1)
正态分布(2)
Dirichlet 函数介绍
Gibbs Sampling 介绍
LDA Introduction
假设检验
假设检验及其应用
统计参数估计
语言模型和序列标注
NLP&统计语言模型
广告定向中的用户分析
精准定向的广告系统
Learning One Million Latent Topics from Billions of Queries
大规模主题模型建模及其在腾讯业务中的应用
SWIG Introduction
Code Review
SVN Introduction
LDA Training System
Introduction to Peacock
人脸对齐技术
M6D Targeting Model
Multi-Layer Perceptron
一起学习 Spark
Scala入门简介
Akka介绍
MLLib: LR & NB
MLLib: LinearSVM
MLLib: Regression
2.  其他资料整理
本文链接：资料分享本站文章若无特别说明，皆为原创，转载请注明来源：火光摇曳，谢谢！^^

五

http://yimiwawa.github.io/六  ffmpeg SDLhttp://dranger.com/ffmpeg/

6 

http://visioncompute.readthedocs.org/en/latest/FaceDetect.html

七

http://weibo.com/cvrobot?is_hot=1&noscale_head=1#_0

八  http://bigwww.epfl.ch/

http://imagingbook.com/source/

http://imagingbook.com/9 https://www.behance.net/gallery/29828109/Deep-Learning-Automatic-Parking-Lot-Classification 

10 http://blog.csdn.net/huneng1991/article/details/48085601