Unsupervised Learning Approach for Clustering Leaf Images

Autor:	G Chamundeswari
Rok vydání:	2021
Předmět:	Computer science business.industry Unsupervised learning Pattern recognition Artificial intelligence Cluster analysis business
Zdroj:	IOP Conference Series: Materials Science and Engineering. 1074:012020
ISSN:	1757-899X 1757-8981
DOI:	10.1088/1757-899x/1074/1/012020
Popis:	With appropriate representation methods, the clustering techniques are found to be efficient with neural networks. The present work aims to propose various feature representation techniques for efficient clustering. The methods used for feature representation in this paper are, a method using random closed set, a method using edge information of input entity, a method that uses Huff transformation and a method that uses boundary moments. A comparative study of these representation methods for clustering the input objects using artificial neural networks, specifically Self-Organizing Map (SOM) is focused.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c6f955af7523f4a10dcf84fa9fc6217b https://doi.org/10.1088/1757-899x/1074/1/012020 Zobrazit plný text záznamu