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Document Type : Latin Dissertation
Language of Document : English
Record Number : 148552
Doc. No : ET20344
Main Entry : AMIT SETHI
Title Proper : INTERACTION BETWEEN MODULES IN LEARNING SYSTEMS FOR VISION APPLICATIONS
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Complex vision tasks such as event detection in a surveillance video can be divided into subtaskssuch as human detection, tracking, recognition, and trajectory analysis. The video can be thought ofas being composed of various features. These features can be roughly arranged in a hierarchy fromlow-level features to high-level features. Low-level features include edges and blobs, and high-levelfeatures include objects and events. Loosely, the low-level feature extraction is based on signallimageprocessing techniques, while the high-level feature extraction is based on machine learning techniques.Traditionally, vision systems extract features in a feedforward manner on the hierarchy; that is,certain modules extract low-level features and other modules make use of these low-level features toextract high-level features. Along with others in the research community we have worked on this designapproach. We briefly present our work on object recognition and multiperson tracking systems designed.
Subject : Electericl tess
: برق
electronic file name : TL43471.pdf
Title and statement of responsibility and : INTERACTION BETWEEN MODULES IN LEARNING SYSTEMS FOR VISION APPLICATIONS [Thesis]
 
 
 
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