face authentication Training
标签： authentication Training face
上传时间： 2014-01-08
上传用户：wangzhen1990
《Google Cluster Computing Faculty Training Workshop》讲义，对Google技术感兴趣可看一下
标签： Computing Training Workshop Cluster
上传时间： 2014-01-13
上传用户：Zxcvbnm
Training and then recognition of a spesified word in MATLAB
标签： recognition spesified Training MATLAB
上传时间： 2013-12-06
上传用户：cx111111
spnet can be used for Training neural network
标签： Training network neural spnet
上传时间： 2013-11-29
上传用户：gmh1314
mobile station Training material
标签： material Training station mobile
上传时间： 2017-09-09
上传用户：gououo
lynda.com 2007年出品的javascript essential Training教学视频(Dori Smith主讲)的配套源码。
标签： javascript essential Training lynda
上传时间： 2013-11-28
上传用户：yuzsu
Allegro® PCB SI 官方培训教程，以15..5版本为例进行讲解
标签： Allegro-PCB-SI-Foundations-Traini ng-Manual
上传时间： 2013-06-02
上传用户：dhb717
Methods for designing a maintenance simulation Training system for certain kind of radio are introduced. Fault modeling method is used to establish the fault database. The system sets up some typical failures， follow the prompts trainers can locate the fault source and confirm the type to accomplish corresponding fault maintenance Training. A Training evaluation means is given to examining and evaluating the Training performance. The system intuitively and vividly shows the fault maintenance process， it can not only be used in teaching， but also in daily maintenance Training to efficiently improve the maintenance operation level. Graphical programming language LabVIEW is used to develop the system platform.
上传时间： 2013-11-19
上传用户：3294322651
最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast Training of support vector machines using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the Generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999.
上传时间： 2013-12-16
上传用户：亚亚娟娟123
LVQ学习矢量化算法源程序 This directory contains code implementing the Learning vector quantization network. Source code may be found in LVQ.CPP. Sample Training data is found in LVQ1.PAT. Sample test data is found in LVQTEST1.TST and LVQTEST2.TST. The LVQ program accepts input consisting of vectors and calculates the LVQ network weights. If a test set is specified, the winning neuron (class) for each neuron is identified and the Euclidean distance between the pattern and each neuron is reported. Output is directed to the screen.
标签： implementing quantization directory Learning
上传时间： 2015-05-02
上传用户：hewenzhi
