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Home / programming language / Online Matlab Projects / False Discovery Rate Approach to Unsupervised Image Change Detection
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Matlab Project - DIP, final year projects.
  • Matlab Project - DIP, final year projects.

False Discovery Rate Approach to Unsupervised Image Change Detection

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SKU: PROJ7373 Categories: 2017 Projects, Digital Image Processing Projects, Online Matlab Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Java Project Code, Matlab Project, PHP Project, Students Projects
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False Discovery Rate Approach to Unsupervised
Image Change Detection

Abstract— the problem of unsuper-vised change detection on two or more coregistered images of
the same object or scene at several time instants. We propose a novel empirical-Bayesian approach that is based on a false discovery rate formulation for statistical inference on local patch-based samples. This alternative error metric allows to efficiently adjust the family-wise error rate in case of the considered large-scale testing problem. The designed change detector operates in an unsupervised manner under the assumption of the limited amount of changes in the analyzed imagery. The detection is based on the use of various statistical features, which enable the detector to address application-specific detection problems provided an appropriatead hoc feature choice. < final year projects >

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