Pattern Recognition and Machine Learning(完整答案),课后答案,模式识别与机器学习
2019-12-21 19:59:49 1.42MB PRML 课后答案 高清版
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face_recognition(人脸识别),face_recognition(人脸识别),供大家参考。
2019-12-21 19:54:21 14.37MB 人脸识别
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Pattern Recognition and Machine Learning. Bishop. 英文版 完整版pdf
2019-12-21 19:51:39 8.64MB PRML
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机器学习经典书籍,PRML,Pattern Recognition And Machine Learning,和课后习题答案
2019-12-21 19:47:46 8.71MB PRML 英文 课后习题 答案
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李子青的人脸识别手册 包含人脸检测、人脸跟踪、人脸识别方面的内容。
2019-12-21 19:46:42 12.06MB 人脸识别 李子青
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Face Recognition 是一个基于 Python 的人脸识别库,它还提供了一个命令行工具,让你通过命令行对任意文件夹中的图像进行人脸识别操作。 该库使用 dlib 顶尖的深度学习人脸识别技术构建,在户外脸部检测数据库基准(Labeled Faces in the Wild benchmark)上的准确率高达 99.38%。
2019-12-21 19:43:59 10.57MB Python 人脸识 人工智能
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For those entering the field of artificial neural networks, there has been an acute need for an authoritative textbook that explains the main ideas clearly and consistently using the basic tools of linear algebra, calculus, and simple probability theory. There have been many attempts to provide such a text, but until now, none has succeeded. Some authors have failed to separate the basic ideas and principles from the soft and fuzzy intuitions that led to some of the models as well as to most of the exaggerated claims. Others have been unwilling to use the basic mathematical tools that are essential for a rigorous understanding of the material. Yet others have tried to cover too many different kinds of neural network without going into enough depth on any one of them. The most successful attempt to date has been "Introduction to the Theory of Neural Computation" by Hertz, Krogh and Palmer. Unfortunately, this book started life as a graduate course in statistical physics and it shows. So despite its many admirable qualities it is not ideal as a general textbook.
2019-12-21 19:42:59 22.44MB neural network pattern recognition
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书籍,介绍wfst在语音识别中的应用教程。讲得十分详细,值得一读。
2019-12-21 19:42:16 1.33MB wfst
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A tutorial on support vector machines for pattern recognition 的原文和对应的中文翻译 是SVM最为经典的资料之一
2019-12-21 19:38:30 987KB SVM 支持向量机 经典 资料
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这本模式识别的书非常经典,然而也非常稀罕,很少有人有。我最早读的是第二版,这本书全面覆盖了统计模式识别领域的重要知识点。书中用大量篇幅讲解无监督聚类方法,这一点在模式识别教材中应该是独一无二的,比如Duda的书在这方面只留了一章,处理的也比较简单。另外,本书还有章节专门讲特征抽取、选择,以及模板匹配这些内容,也弥补了Duda教材的不足。第三版增加了一些内容,主要是基于核方法的内容,反映了学界的进展。-Book of this pattern recognition is very classic, however, very rare, very few people have. I first read the second edition, this book comprehensively covers the important points of the field of statistical pattern recognition. Book at great length to explain the unsupervised clustering method, which is unique in pattern recognition textbooks, such as Duda' s book in this regard, leaving only one chapter, is also relatively simple to deal with. In addition, the book there are chapters dedicated speakers feature extraction, selection, and template matching, but also compensate for the lack of materials Duda. The third edition of the increase in some of the content is mainly based on the content of the kernel method, reflecting the academic progress.
2019-12-21 19:33:02 19.52MB 模式识别 机器学习
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