A MACHINE LEARNING APPROACH TO CONTENT-BASED IMAGE INDEXING AND RETRIEVAL

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" A MACHINE LEARNING APPROACH TO CONTENT-BASED IMAGE INDEXING AND RETRIEVAL "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	149677
Doc. No	:	ET21469
Main Entry	:	Yixin Chen
Title Proper	:	A MACHINE LEARNING APPROACH TO CONTENT-BASED IMAGE INDEXING AND RETRIEVAL
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	In various application domains such as entertainment, biomedicine, commerce,education, and crime prevention, the volume of digital data archives is growing rapidly.The very large repository of digital information raises challenging problems in retrievaland various other information manipulation tasks. Content-based image retrieval (CBIR)is aimed at efficient retrieval of relevant images from large image databases based onautomatically derived imagery features. However, images with high feature similaritiesto the query image may be very different from the query in terms of semantics. Thisdiscrepancy between low-level content features (such as color, texture, and shape) andhigh-level semantic concepts (such as sunset, flowers, outdoor scene, etc.) is known astested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL44638.pdf
Title and statement of responsibility and	:	A MACHINE LEARNING APPROACH TO CONTENT-BASED IMAGE INDEXING AND RETRIEVAL [Thesis]