Search Deep learning, 300 result(s) found

adaboost for machine learning, object classification and detection based tracking

AdaBoost, short for "Adaptive Boosting", is a machine learning algorithm formulated by Yoav Freund and Robert Schapire[1] who won the prestigious "Gödel Prize" in 2003 for their work.[2] It is ameta-algorithm, and can be used in conjunction with many other le...

Machine learning method of SVM training

SVM SVM (Support Vector Machine) as a training machine learning methods, relying on small sample learning guide Star model parameters extracted can be evenly distributed and stars a greatly reduced number of guide star catalog Vapnik et al in the years examined in the context of statistical lear...

iterative learning control

This article proposes a betterment process for the operation of a mechanical robot in a sense that it betters the next operation of a robot by using the previous operation’s data. The process has an iterative learning structure such that the (k + 1)th input to joint actuators consists of the k...

perceptron learning algorithm

In machine learning, the perceptron is an algorithm for supervisedclassification of an input into one of several possible non-binary outputs. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor f...

Cloud Computing through Mobile learning

The development of computer networktechnology and mobile communicationtechnology, a newkind of distance education mode, Mobile learning (M-learning),was created. Mobile learning isconsidered the next step of onlinelearning by incorporating mobility as a keyrequirement.Indeed, the current wide spread...

Speech learning in Matlab

Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, Switzerland. The toolbox is written in a mix of Python and C++ and is designed to be both efficient and reduce development time. • To learn about this projec...

Network parameter learning of Bayesian

Parameter learning of Bayesian network, sprinkler model, classic models, integrated code m file, em algorithm, is not original....

Implementing search wide and Deep (artificial intelligence) using python

This paper presents the development of search depth and width used in artificial intelligence.  The implementation used Python....

Machine learning Source

This is the real part of the code of machine learning, pro-test available. . . More suitable for study entry. . . . Very good. . . Now just uploaded a part of the source code, after the future will continue to upload up. . . I hope you learn and progress together. . . . ....

Multiple-instance learning algorithm based on semi-supervised SVM

MissSVM is a package for solving multi-instance learning problems using semi-supervised support vector machines. The purpose of MissSVM is to show that if the assumption of i.i.d. instances were taken, multi-instance learning can be viewed as a special case of semi-supervised learning, and the field...

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