A Novel Approach to Fish Disease Diagnostic System based on Machine Learning
Journal Title: Advances in Image and Video Processing - Year 2017, Vol 5, Issue 1
Abstract
Real-Time identification automated system diagnoses fish disease i.e. Epizootic Ulcerative syndrome (EUS) which is caused by Aphanomyces invadans, a fungal pathogen. In this paper we propose a Real- Time fish disease diagnose system with better accuracy. In order to improve the accuracy we propose a combination (PCA-FAST-NN) which combine the Principle component analysis (PCA) with Features from Accelerated Segment Test (FAST)feature detector using Machine Learning Algorithm(Neural Network) i.e. (PCA-FAST-NN) .The Experimentation has been done on the real images of Epizootic Ulcerative syndrome (EUS) infected fish database and implemented in MATLAB environment.
Authors and Affiliations
Shaveta Malik, Tapas Kumar, A. K Sahoo
Keywords
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- EP ID EP303236
- DOI 10.14738/aivp.51.2809
- Views 87
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