Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin

Underwater world had always been full of mystery in view of the fact that it was filled with unaccountably many species. Among the living organisms, fish are the most familiar to humans in environment, commercial and even recreational. From this perspective, fish recognition arouses interest of n...

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Main Author:	Nordin, Muhamad Syafiq
Format:	Thesis
Language:	English
Published:	Faculty of Computer and Mathematical Sciences 2007
Subjects:	Electronic computers. Computer science
Online Access:	http://ir.uitm.edu.my/id/eprint/1696/ http://ir.uitm.edu.my/id/eprint/1696/1/TD_MUHAMAD%20SYAFIQ%20NORDIN%20CS%2007_5%20P01.pdf

id	uitm-1696
recordtype	eprints
spelling	uitm-16962019-07-22T02:56:05Z http://ir.uitm.edu.my/id/eprint/1696/ Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin Nordin, Muhamad Syafiq Electronic computers. Computer science Underwater world had always been full of mystery in view of the fact that it was filled with unaccountably many species. Among the living organisms, fish are the most familiar to humans in environment, commercial and even recreational. From this perspective, fish recognition arouses interest of not only dedicated underwater scientists but also of ordinary people who may be interested in this matter. Roughly 1.4 million species are known to science. Beyond this estimation, most unrecognized species are in poorly studied groups where it habitats were seldom explored. The job of discovering new species falls on the area of biology called taxonomy. The World-Wide Web is being used to collect data used by taxonomists' for instance taxonomic literature and specimen databases in different parts of the globe, archived as digital images. This scenario had shown us that there is a need for an animal recognition tool that supports efficient searching and navigating through large image databases of specimens. In this research, a prototype of animal recognition application using Kohonen Feature Map was introduced. The system has a learning component that able to classify fish species based on the local visual feature of its representative image. This research also reveals Kohonen Feature Map as a promising tool for image classification. Realized that there is millions of species around the globe, this research focused on fish species that was common in Malaysia. 20 species were studied in this research. The image database used in the research was composed of 100 color images Faculty of Computer and Mathematical Sciences 2007 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/1696/1/TD_MUHAMAD%20SYAFIQ%20NORDIN%20CS%2007_5%20P01.pdf Nordin, Muhamad Syafiq (2007) Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin. Degree thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Electronic computers. Computer science
spellingShingle	Electronic computers. Computer science Nordin, Muhamad Syafiq Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
description	Underwater world had always been full of mystery in view of the fact that it was filled with unaccountably many species. Among the living organisms, fish are the most familiar to humans in environment, commercial and even recreational. From this perspective, fish recognition arouses interest of not only dedicated underwater scientists but also of ordinary people who may be interested in this matter. Roughly 1.4 million species are known to science. Beyond this estimation, most unrecognized species are in poorly studied groups where it habitats were seldom explored. The job of discovering new species falls on the area of biology called taxonomy. The World-Wide Web is being used to collect data used by taxonomists' for instance taxonomic literature and specimen databases in different parts of the globe, archived as digital images. This scenario had shown us that there is a need for an animal recognition tool that supports efficient searching and navigating through large image databases of specimens. In this research, a prototype of animal recognition application using Kohonen Feature Map was introduced. The system has a learning component that able to classify fish species based on the local visual feature of its representative image. This research also reveals Kohonen Feature Map as a promising tool for image classification. Realized that there is millions of species around the globe, this research focused on fish species that was common in Malaysia. 20 species were studied in this research. The image database used in the research was composed of 100 color images
format	Thesis
author	Nordin, Muhamad Syafiq
author_facet	Nordin, Muhamad Syafiq
author_sort	Nordin, Muhamad Syafiq
title	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_short	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_full	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_fullStr	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_full_unstemmed	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_sort	animal recognition application using kohonen feature map / muhamad syafiq nordin
publisher	Faculty of Computer and Mathematical Sciences
publishDate	2007
url	http://ir.uitm.edu.my/id/eprint/1696/ http://ir.uitm.edu.my/id/eprint/1696/1/TD_MUHAMAD%20SYAFIQ%20NORDIN%20CS%2007_5%20P01.pdf
first_indexed	2023-09-18T22:46:11Z
last_indexed	2023-09-18T22:46:11Z
_version_	1777417240269815808

Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin

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