Open AccessClassificação de Espécies de Plantas Usando Extreme Learning Machine
Author(s) -
Larissa Britto,
Luciano D. S. Pacífico
Publication year - 2019
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/eniac.2019.9268
Subject(s) - extreme learning machine , computer science , artificial intelligence , feature extraction , machine learning , task (project management) , artificial neural network , identification (biology) , pattern recognition (psychology) , feature (linguistics) , engineering , linguistics , philosophy , botany , systems engineering , biology
Plants play an important role in nature, but correct plant species identification is still a challenging task for non-specialized people. Many works have been proposed towards the development of automatic plant species recognition systems through Machine Learning methods, but most of them lack the proper experimental analysis. In this work, we evaluate the performance of a general-purpose Artificial Neural Network to perform plant classification task: the Extreme Learning Machine (ELM).We compare ELM with several classifiers from plant recognition literature by means of three real-world data sets obtained from different image processing and feature extraction processes. A statistical hypothesis test is employed to perform proper experimental evaluation.