Feature Extraction and Machine Learning for the Classification of Brazilian Savannah Pollen Grains

The classification of pollen species and types is an important task in many areas like forensic palynology, archaeological palynology and melissopalynology. This paper presents the first annotated image dataset for the Brazilian Savannah pollen types that can be used to train and test computer visio...

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Veröffentlicht in:	PloS one Jg. 11; H. 6; S. e0157044
Hauptverfasser:	Gonçalves, Ariadne Barbosa, Souza, Junior Silva, Silva, Gercina Gonçalves da, Cereda, Marney Pascoli, Pott, Arnildo, Naka, Marco Hiroshi, Pistori, Hemerson
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 08.06.2016 Public Library of Science (PLoS)
Schlagworte:	Accuracy Archaeology Artificial intelligence Automation Biology and Life Sciences Biotechnology Brazil Classification Computer and Information Sciences Computer science Computer vision Criminal investigations Data mining Environmental science Feature extraction Forensic engineering Forensic science Grassland Honey Human performance Identification Identification and classification Information retrieval Learning algorithms Machine Learning Medicine and Health Sciences Palynology Physiological aspects Pollen Pollen - anatomy & histology Pollen - classification Research and Analysis Methods Researchers Savannahs Species classification Sustainability Wavelet transforms Brazil
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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