搜索资源列表
facedetect_harrcascade
- 基于adaboost的构造的cascade用于快速检测人脸，能够实时检测视频中的人脸。没有采用opencv的代码。-Adaboost based on the structure of the cascade for the rapid detection of human faces, real-time video can face. Did not use the code opencv.
abr_v1[1].tar
- Adaboost_rbf算法，matlab实现。希望对您有参考价值-adaboost algorithm in matlab
GML_AdaBoost_Matlab_Toolbox_0[1].3
- 该文件里面包含了三个AdaBoost算法，使用非常方便-The document which contains three AdaBoost algorithm, is very convenient to use
AdaBoost_RandomForest_4
- adaboost code in matlab
adaboost
- adaboost implementation in matlab
AdaBoost_weaklearner_1
- it is an adaboost weak learner
Adaboost2004
- 基于Adaboost的快速人脸跟踪算法2004，该算法具有较强的自适应性-Adaboost-based fast algorithm for face tracking in 2004, the algorithm has strong adaptability
AdaBoost_weaklearner_1
- adaboost training for select weak classifier.
wenj
- adaboost FEATURE SELECTION USING ADABOOST FOR FACE EXPRESSION RECOGNITION-FEATURE SELECTION USING ADABOOST FOR FACE EXPRESSION RECOGNITION
ada_2.0-1
- Adaboost，一种很流行的机器学习算法。用matlab实现的。-Adaboost, a very popular machine learning algorithm. Achieved using matlab.
Adaboost
- 几篇关于人脸检测和识别方面的文章 基于adaboost方法-A few on the face detection and identification methods Based on the adaboost
ADABOOSTTUTX
- tITORIAL aDABOOST (BOOSTING)
adaboost
- 人脸识别，基于MATLAB的一个人脸识别训练样本-recognition of face
train_v2
- 一个基于adaboost的人脸检测分类器训练程序，用MATLAB写的，希望能和大家分享-a face detect programme based on adaboost which is written by matlab
ABdemo
- 下载别人的基于 AdaBoost 人脸检测源代码 供大家一起学习-Download others AdaBoost-based face detection source code for everyone to learn
Adaboost_Tutorial
- Adaboost算法的介绍，经典的文章，帮助大家理解-Adaboost algorithm, the classic articles, help us to understand
fdp-v51
- Face detection project based on Adaboost algorithum.
Rapidobjectdetection
- 详细介绍了基于adaboost的人脸检测算法，是adaboost用于图像检测的经典文档-Details of the adaboost based on face detection algorithm is used for image detection adaboost classic document
adaboostAndSVM
- adaboost和SVM的文章.可能学习人脸识别或者模式识别的朋友们需要。也是来自于网络。-adaboost classifiers, and svm doc.from internet。
boosting-survey
- Boosting is a general method for improving the accuracy of any given learning algorithm. Focusing primarily on the AdaBoost algorithm, this chapter overviews some of the recent work on boosting including analyses of AdaBoost’s training error an