模式识别1新 优质课件
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• Pattern recognition is a very broad subject with many applications
• In this course we will study a variety of techniques to solve P.R. problems and discuss their relative strengths and weaknesses
Ray Kurzweil, NY Times, Nov 24, 2003
2019/12/4
5
What is a Pattern?
“A pattern is the opposite of a chaos; it is an entity vaguely defined, that could be given a name.” (Watanabe)
模式识别原理
华中科技大学图像识别与人工智能研究所 图像分析与智能系统研究室 曹治国
2019/12/4
1
教材及参考书
来自百度文库
模式分类
• Duda等 机械工业出版社
现代模式识别
• 孙即祥等 国防科技大学出版社
模式识别
• 边肇祺等 清华大学出版社
模式识别导论
• 李金宗
高等教育出版社
2019/12/4
2019/12/4
8
模式识别 待识别的对象 抽象 数学模型
描述和代替识别对象
对象的描述 模式
特征矢量 符号串/图
数学表达式
事物的代表
事物的数学模型之一
2019/12/4
9
Intra-class and Inter-class Variability
The letter “T” in different typefaces
Having been shown a few positive examples (and perhaps a few negative examples) of a pattern class, the system “learns” to tell whether or not a new object belongs in this class (Watanabe)
Pattern Recognition
Pattern Recognition Letters
Machine Learning
2019/12/4
4
Pattern Recognition
“The real power of human thinking is based on recognizing patterns. The better computers get at pattern recognition, the more humanlike they will become”.
2
授课方式
课堂讲授与讨论
考核方式
笔试 实验及报告
----70% ----30%
2019/12/4
3
期刊
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Pattern Recognition and Artificial Intelligence
2019/12/4
6
Recognition
Identification of a pattern as a member of a category we already know, or we are familiar with Classification (known categories) &
Problem Speech recognition
Non-destructive testing
Detection and diagnosis of disease
Natural resource identification Aerial reconnaissance
Character recognition (page readers, zip code, license plate)
Inferring a generality from a few exemplars
COGNITION = Formation of new classes
RECOGNITION = known classes
2019/12/4
14
Pattern Recognition Applications
Same face under different expression, pose….
2019/12/4
12
Interclass Similarity
Identical twins
2019/12/4
Characters that look similar
13
Pattern Recognition
Types of cardiac conditions, classes of brain conditions
Multispectral images
Terrain forms, vegetation cover
Visual, infrared, radar images
Tanks, airfields
Input
Output
Speech waveforms
Spoken words, speaker identity
Ultrasound, eddy current, Presence/absence of flaw, acoustic emission waveforms type of flaw
EKG, EEG waveforms
Clustering (creation of new categories)
Category “A”
Category “B”
Classification
2019/12/4
Clustering
7
Pattern Recognition
• Given an input pattern, make a decision about the “category” or “class” of the pattern
• In this course we will study a variety of techniques to solve P.R. problems and discuss their relative strengths and weaknesses
Ray Kurzweil, NY Times, Nov 24, 2003
2019/12/4
5
What is a Pattern?
“A pattern is the opposite of a chaos; it is an entity vaguely defined, that could be given a name.” (Watanabe)
模式识别原理
华中科技大学图像识别与人工智能研究所 图像分析与智能系统研究室 曹治国
2019/12/4
1
教材及参考书
来自百度文库
模式分类
• Duda等 机械工业出版社
现代模式识别
• 孙即祥等 国防科技大学出版社
模式识别
• 边肇祺等 清华大学出版社
模式识别导论
• 李金宗
高等教育出版社
2019/12/4
2019/12/4
8
模式识别 待识别的对象 抽象 数学模型
描述和代替识别对象
对象的描述 模式
特征矢量 符号串/图
数学表达式
事物的代表
事物的数学模型之一
2019/12/4
9
Intra-class and Inter-class Variability
The letter “T” in different typefaces
Having been shown a few positive examples (and perhaps a few negative examples) of a pattern class, the system “learns” to tell whether or not a new object belongs in this class (Watanabe)
Pattern Recognition
Pattern Recognition Letters
Machine Learning
2019/12/4
4
Pattern Recognition
“The real power of human thinking is based on recognizing patterns. The better computers get at pattern recognition, the more humanlike they will become”.
2
授课方式
课堂讲授与讨论
考核方式
笔试 实验及报告
----70% ----30%
2019/12/4
3
期刊
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Pattern Recognition and Artificial Intelligence
2019/12/4
6
Recognition
Identification of a pattern as a member of a category we already know, or we are familiar with Classification (known categories) &
Problem Speech recognition
Non-destructive testing
Detection and diagnosis of disease
Natural resource identification Aerial reconnaissance
Character recognition (page readers, zip code, license plate)
Inferring a generality from a few exemplars
COGNITION = Formation of new classes
RECOGNITION = known classes
2019/12/4
14
Pattern Recognition Applications
Same face under different expression, pose….
2019/12/4
12
Interclass Similarity
Identical twins
2019/12/4
Characters that look similar
13
Pattern Recognition
Types of cardiac conditions, classes of brain conditions
Multispectral images
Terrain forms, vegetation cover
Visual, infrared, radar images
Tanks, airfields
Input
Output
Speech waveforms
Spoken words, speaker identity
Ultrasound, eddy current, Presence/absence of flaw, acoustic emission waveforms type of flaw
EKG, EEG waveforms
Clustering (creation of new categories)
Category “A”
Category “B”
Classification
2019/12/4
Clustering
7
Pattern Recognition
• Given an input pattern, make a decision about the “category” or “class” of the pattern