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Description: 情感语音合成的经典文章，MIT的博士论文-Emotional Speech Synthesis classic article, MIT doctoral dissertation
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Author: rita |
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Description: 人工智能(Artificial Intelligence，AI)一直都处于计算机技术的最前沿，经历了几起几落…… 长久以来，人工智能对于普通人来说是那样的可望而不可及，然而它却吸引了无数研究人员为之奉献才智，从美国的麻省理工学院(MIT)、卡内基-梅隆大学(CMU)到IBM公司，再到日本的本田公司、SONY公司以及国内的清华大学、中科院等科研院所，全世界的实验室都在进行着AI技术的实验。不久前，著名导演斯蒂文斯皮尔伯格还将这一主题搬上了银幕，科幻片《人工智能》(A.I.)对许多人的头脑又一次产生了震动，引起了一些人士了解并探索人工智能领域的兴趣。-err
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Size: 10240 |
Author: 陶臻 |
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Description: 基于支持向量机的人脸检测训练集增强算法实现。根据支持向量机(support vector machine，简称SVM)~ ，对基于边界的分类算"~(geometric approach)~
言，类别边界附近的样本通常比其他样本包含有更多的分类信息．基于这一基本思路，以人脸检测问题为例．探讨了
对给定训练样本集进行边界增强的问题，并为此而提出了一种基于支持向量机和改进的非线性精简集算法
IRS(improved reduced set)的训练集边界样本增强算法，用以扩大-91l练集并改善其样本分布．其中，所谓IRS算法是指
在精简集(reduced se0算法的核函数中嵌入一种新的距离度量一一图像欧式距离一一来改善其迭代近似性能，IRS
可以有效地生成新的、位于类别边界附近的虚拟样本以增强给定训练集．为了验证算法的有效性，采用增强的样本
集训练基于AdaBoost的人脸检测器，并在MIT+CMU正面人脸测试库上进行了测试．实验结果表明通过这种方法
能够有效地提高最终分类器的人脸检测性能．-According to support vector machines(SVMs)，for those geometric approach based classification
methods，examples close to the class boundary usually are more informative than others．Taking face detection as an
example，this paper addresses the problem of enhancing given training set and presents a nonlinear method to tackle
the problem effectively．Based on SVM and improved reduced set algorithm (IRS)，the method generates new
examples lying close to the face／non—face class boundary to enlarge the original dataset and hence improve its
sample distribution．The new IRS algorithm has greatly improved the approximation performance of the original
reduced set(RS)method by embedding a new distance metric called image Euclidean distance(IMED)into the
keme1 function．To verify the generalization capability of the proposed method，the enhanced dataset is used to train
an AdaBoost．based face detector and test it on the MIT+CMU frontal face test set．The experimental results show
that the origina
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Author: 郭事业 |
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Description: 此文的目的有三个：第一，当地连续均值量化变换特征是提出照明和传感器敏感操作在目标识别上。其次，注册稀疏Winnows网络分割，提出了加快原分类。最后，特点和分类相结合对于正面人脸检测任务。检测结果列
为MIT + CMU系统和BioID数据库。关于这人脸检测器，接收器操作特征曲线BioID数据库产生最好的结果公布。对于结果麻省理工学院的中央结算系统+数据库相当于国家的最先进的脸探测器。一个人脸检测算法的MATLAB版本可以从http://www.mathworks.com/matlabcentral/fileexchange/
loadFile.do？的ObjectID = 13701＆的objectType =FILE下载。
-The purpose of this paper is threefold: firstly, the local Successive
Mean Quantization Transform features are proposed for illumination
and sensor insensitive operation in object recognition. Secondly, a
split up Sparse Network of Winnows is presented to speed up the
original classifier. Finally, the features and classifier are combined
for the task of frontal face detection. Detection results are presented
for the MIT+CMU and the BioID databases. With regard to this
face detector, the Receiver Operation Characteristics curve for the
BioID database yields the best published result. The result for the
CMU+MIT database is comparable to state-of-the-art face detectors.
A Matlab version of the face detection algorithm can be downloaded
from http://www.mathworks.com/matlabcentral/fileexchange/
loadFile.do?objectId=13701&objectType=FILE.
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Size: 1397760 |
Author: 霞 |
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Description: 本文应用SMQT和 SPLIT UP SNOW 分类器来完成对人脸的检测。-The purpose of this paper is threefold: firstly, the local Successive
Mean Quantization Transform features are proposed for illumination
and sensor insensitive operation in object recognition. Secondly, a
split up Sparse Network of Winnows is presented to speed up the
original classifier. Finally, the features and classifier are combined
for the task of frontal face detection. Detection results are presented
for the MIT+CMU and the BioID databases. With regard to this
face detector, the Receiver Operation Characteristics curve for the
BioID database yields the best published result. The result for the
CMU+MIT database is comparable to state-of-the-art face detectors.
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Size: 1561600 |
Author: 吴绪周 |
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