Data/hora: 05/06/2024 11:19:19

Biblioteca(s): 	Embrapa Instrumentação.	
Data corrente: 	09/06/2022	
Data da última atualização: 	23/01/2024	
Autoria: 	NEVES, R. A.; CRUVINEL, P. E.	
Afiliação: 	PAULO ESTEVAO CRUVINEL, CNPDIA.	
Título: 	Application of image processing and advanced intelligent computing for determining stage of Asian rust in soybean plants.	
Ano de publicação: 	2022	
Fonte/Imprenta: 	In: IEEE International Conference on Semantic Computing (ICSC), 16th, Laguna Hills, CA, USA, 2022.	
Páginas: 	280 - 286	
ISBN: 	978-1-6654-3418-8	
ISSN: 	2325-6516	
DOI: 	10.1109/ICSC52841.2022.00053	
Idioma: 	Inglês	
Conteúdo: 	This paper presents a new method that uses the advanced techniques of digital image processing and computational intelligence for monitoring and identifying the stages of Asian rust (Phakopsora pachyrhizi) in soybean plants Glycine max (L.) Merril). Its establishment included organization and structuring of digital images of soybean plant leaves, image preprocessing steps, and segmentation based on the phenomenology of the disease development process with a semantics approach involving agricultural evaluation. The method also required recognition of the patterns appearing on leaves due to the presence of the disease as well as machine learning using a support vector machine for the classification and interpretation of the stages and their evolutions. For the stage of pattern recognition, the techniques of feature extraction scaleinvariant feature transform, Hu invariant moments, and  histogram of oriented gradients were used and principal component analysis was conducted for the dimensionality reduction of the integrated vector of the features. The results of the application of the method showed potential for the monitoring and identification of the stages of the disease for determining the subsidies in the decision-making of production  systems by agricultural producers	
Palavras-Chave: 	Asian soybean rust; Image processing; Machine learning; Semantic segmentation.	
Categoria do assunto: 	--	
Registro original: 	Embrapa Instrumentação (CNPDIA)	
Exemplares: 	CNPDIA - (18018-1) - UPC - PC - DD - PROCI.22/63 -  - 2022-68 - DIS