Number of the records: 1

Towards Discrimination of Plant Species by Machine Vision: Advanced Statistical Analysis of Chlorophyll Fluorescence Transients

SYSNO ASEP	0341134
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Towards Discrimination of Plant Species by Machine Vision: Advanced Statistical Analysis of Chlorophyll Fluorescence Transients
Author(s)	Mishra, Kumud (UEK-B)_{RID, ORCID, SAI}
Number of authors	4
Source Title	Journal of Fluorescence. - : Springer - ISSN 1053-0509 Roč. 5, č. 19 (2009), s. 905-913
Number of pages	9 s.
Language	eng - English
Country	US - United States
Keywords	ARTIFICIAL NEURAL-NETWORKS ; FEATURE-SELECTION ; WEED DETECTION
Subject RIV	CE - Biochemistry
CEZ	AV0Z60870520 - UEK-B (2005-2011)
UT WOS	000269954700017
Annotation	Automatic discrimination of plant species is required for precision farming and for advanced environmental protection. Here, we investigated the discriminative potential of chlorophyll fluorescence imaging in a case study using three closely related plant species of the family Lamiaceae. We compared discriminative potential of eight classifiers and four feature selection methods to identify the fluorescence parameters that can yield the highest contrast between the species. The ability of the combinatorial statistical techniques for discriminating the species was compared to the resolving power of conventional fluorescence parameters and found to be more efficient.
Workplace	Global Change Research Institute
Contact	Nikola Šviková, svikova.n@czechglobe.cz, Tel.: 511 192 268
Year of Publishing	2010

Number of the records: 1