Method for identifying plant diseases based on monitoring platform for plantations

LISNIC, Dorin; BOSTAN, Viorel; ROTARU, Lilia; CARBUNE, Viorel; KAPUSTEANSKI, Maxim; SEINIC, Valeriu

dc.contributor.author	LISNIC, Dorin
dc.contributor.author	BOSTAN, Viorel
dc.contributor.author	ROTARU, Lilia
dc.contributor.author	CARBUNE, Viorel
dc.contributor.author	KAPUSTEANSKI, Maxim
dc.contributor.author	SEINIC, Valeriu
dc.date.accessioned	2026-02-15T15:11:53Z
dc.date.available	2026-02-15T15:11:53Z
dc.date.issued	2025
dc.identifier.citation	LISNIC, Dorin; Viorel BOSTAN; Lilia ROTARU; Viorel CARBUNE; Maxim KAPUSTEANSKI and Valeriu SEINIC. Method for identifying plant diseases based on monitoring platform for plantations. In: IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2025, Chisinau, Republic of Moldova, 23-26 June, 2025. Technical University of Moldova. Institute of Electrical and Electronics Engineers, 2025, pp. 1-6. ISBN 979-8-3315-3720-3, eISBN 979-8-3315-3719-7, ISSN 2375-8236, eISSN 2687-9808.	en_US
dc.identifier.isbn	979-8-3315-3720-3
dc.identifier.issn	2375-8236
dc.identifier.issn	2687-9808
dc.identifier.issn	979-8-3315-3719-7
dc.identifier.uri	https://doi.org/10.1109/BlackSeaCom65655.2025.11193949
dc.identifier.uri	https://repository.utm.md/handle/5014/35223
dc.description	Acces full text: https://doi.org/10.1109/BlackSeaCom65655.2025.11193949	en_US
dc.description.abstract	This study introduces a deep learning-based system for detecting plant diseases using multispectral image analysis and convolutional neural networks trained on the PlantVillage repository and other datasets, including those provided by Forever, a company specializing in maize hybrids and other plants. The model achieves high accuracy and benefits from GPU acceleration, while a self-learning mechanism ensures adaptability to new conditions and disease types.	en_US
dc.language.iso	en	en_US
dc.publisher	Institute of Electrical and Electronics Engineers	en_US
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	artificial intelligence	en_US
dc.subject	automated classification	en_US
dc.subject	deep learning	en_US
dc.subject	multispectral imaging	en_US
dc.title	Method for identifying plant diseases based on monitoring platform for plantations	en_US
dc.type	Article	en_US