1. 模式识别相关领域
① Machine vision,
② Character (letter or number)recognition—>Optical character recognition (OCR) systems
OCR系统3种典型应用:machine reading of bank checks; automatic mail-sorting machines for postal codeidentification in post offices; Online handwritingrecognition systems
③ Computer-aided diagnosis
④ Speech recognition
⑤ Data mining and knowledge discovery in databases
其他相关:fingerprintidentification, signature authentication, text retrieval, and face and gesturerecognition.
紧密联系的科学学科:linguistics,computer graphics,machine vision, and database design.
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3.非监督学习的主要问题(unsupervised pattern recognition)
A major issue in unsupervisedpattern recognition is that of defining the“similarity” between two featurevectors and choosing an appropriate measure for it. Another issue of importanceis choosing an algorithmic scheme that will cluster (group) the vectors on thebasis of the adopted similarity measure.
4. 半监督学习(Semi-supervised learning)
显得重要:当系统设计者手中只有有限的带标签数据。semi-supervised learning provides an a priori knowledge that theclustering algorithm has to respect.
本文深入探讨了模式识别领域中机器视觉、字符识别、计算机辅助诊断、语音识别等关键技术,以及非监督学习与半监督学习的概念、挑战与应用。通过分析不同领域的实例,阐述了这些技术在实际场景中的价值与潜力。
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