DOI - Vydavatelství Mendelovy univerzity v Brně

Identifikátory DOI

DOI: 10.11118/978-80-7509-990-7-0084

USE OF ANNOTATED IMAGE DATA FOR FRUIT DIVERSITY ANALYSIS

Miroslav Jaroš1, Jiří Podivín1, Petr Pernes1, Oldřich Trenz1
1 Department of Informatics, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic

This paper deals with a method of development of an annotated image dataset for the detection and classification of plant tissues, aimed at supporting automation in agriculture. The work includes a collection of high-definition image data, their annotation and utility scripts, with the aim of creating a universally accessible dataset for the scientific community. The method is designed to be compatible with off-the-shelf hardware, in order to better support research and development in the field of automated plant identification and plant disease diagnostics. This approach has the potential to significantly improve the efficiency of cultivation processes and support the implementation of advanced technologies in the agricultural sector, along with the automation of this sector.

Klíčová slova: image analysis, plant classification, dataset, learning, annotation, image data

stránky: 84-92, online: 2024



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