Data/hora: 01/06/2024 00:55:12

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	14/12/2015	
Data da última atualização: 	21/01/2020	
Autoria: 	VARGAS, J. E.; FALCÃO, A. X.; ESQUERDO, J. C. D. M.; COUTINHO, A. C.; ANTUNES, J. F. G.	
Afiliação: 	Unicamp; UFMG; JULIO CESAR DALLA MORA ESQUERDO, CNPTIA; ALEXANDRE CAMARGO COUTINHO, CNPTIA; JOAO FRANCISCO GONCALVES ANTUNES, CNPTIA.	
Título: 	Contextual superpixel description for remote sensing image classification.	
Ano de publicação: 	2015	
Fonte/Imprenta: 	In: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2015, Milan. Proceedings... Washington, DC: Institute of Electrical and Electronics Engineers, 2015.	
Páginas: 	p. 1132-1135.	
Idioma: 	Inglês	
Notas: 	IGARSS 2015.	
Conteúdo: 	Abstract: The performance of pattern classifiers depends on the separability of the classes in the feature space - a property related to the quality of the descriptors - and the choice of informative training samples for user labeling - a procedure that usually requires active learning. This work is devoted to improve the quality of the descriptors when samples are superpixels from remote sensing images. We introduce a new scheme for superpixel description based on Bag of visual Words, which includes information from adjacent superpixels, and validate it by using two remote sensing images and several region descriptors as baselines.	
Palavras-Chave: 	Contextual information; Superpixel description.	
Thesaurus Nal: 	remote sensing.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (18537-1) - UPC - AA - DD -  -  -  - DIS