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Document Type : Latin Dissertation
Language of Document : English
Record Number : 152429
Doc. No : ET24221
Main Entry : DEXIANG LUO,B.ENG
Title Proper : OCCLUDED OBJECT DISCRIMINATION BY A MODIFIED HOPFIELD NEURAL NETWORKPOMPES PAR TRANSITIONS MULTIPLES
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : This thesis presents a new method of the 2-D partially occluded objectdiscrimination for the computer vision application. A binary modified Hopfield neuralnetwork was applied to perform the global feature matching. To obtain the featurepoints of the object, a Gaussian hction was implemented to smooth the objectboundary curve and a curvature estimation method was used to extract the dominant.
Subject : Electericl tess
: برق
electronic file name : TL48423.pdf
Title and statement of responsibility and : OCCLUDED OBJECT DISCRIMINATION BY A MODIFIED HOPFIELD NEURAL NETWORKPOMPES PAR TRANSITIONS MULTIPLES [Thesis]
 
 
 
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