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人脸检测。用c++编写。人脸检测是人脸分析的首要环节,其处理的问题是确认图像(或影像)中是
否存在人脸,如果存在则对人脸进行定位。人脸检测的应用领域相当广泛,是实
现机器智能化的重要步骤之一。
AdaBoost 算法是1995 年提出的一种快速人脸检测算法,是人脸检测领域里
程碑式的进步,这种算法根据弱学习的反馈,适应性地调整假设的错误率,使在
效率不降低的情况下,检测正确率得到了很大的提高。-Face Detection. Using c++ to prepare. Fac
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MultiBoost 是c++实现的多类adaboost酸法。与传统的adaboost算法主要解决二类分类问题不同,MultiBoost解决的是多类的分类问题,而并不是把多类转化成二类问题。-MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning
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这里不光有AdaBoost算法本身的实现,而且还包含利用特征模板从人脸提取特征值的代码,让大家轻松掌握利用AdaBoost进行人脸识别的全过程。-AdaBoost algorithm here not only has its own implementation, but also includes the use of the characteristics of the template from the extracted features of face value of the c
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这片论文描述了动态物体的特征跟踪,用到了15个框架。拥有很强的适应性和跟踪能力。作为人脸识别,模式识别,动态跟踪的开发人员,有很好的参考价值。用c++编写,如果用OpenCV更好-This paper describes a visual object detection framework that is capable of processing
images extremely rapidly while achieving high detection rates. There ar
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静态人脸检测程序。基于Adaboost的检测算法,使用OpenCV中提供的函数在Visual C++2005中实现一个人脸检测程序。-Static face detection process. Adaboost-based detection algorithm using OpenCV provides a function to implement a face detection program in Visual C++2005 in.
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adaboost算法的C语言源代码,大牛编写,很有参考价值-adaboost algorithm C language source code, written in large cattle, great reference value
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Design a feedforward network is u
dehaze algorithms review
path planning using GA and ACO...
The neural network adaboost stron
TS neural network m files, fast c
bp neural network, written with C
Bayes net and memory based learni
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1下载:
Design a feedforward network is u
dehaze algorithms review
path planning using GA and ACO...
The neural network adaboost stron
TS neural network m files, fast c
bp neural network, written with C
Bayes net and memory based learni
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该Adaboost算法用C++实现的基本Adaboost算法,对于初学Adaboost算法和理解Adaboost算法的学生有一定的帮助!如发现我代码中存在错误或不足,欢迎指正,谢谢!-The basic Adaboost algorithm Adaboost algorithm implemented with C++, Adaboost algorithm for beginners and students understand Adaboost algorithm will certain
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