Evaluating deep convolutional neural networks as texture feature extractors (2019)
- Authors:
- USP affiliated authors: BRUNO, ODEMIR MARTINEZ - IFSC ; SCABINI, LEONARDO FELIPE DOS SANTOS - IFSC ; CONDORI, RAYNER HAROLD MONTES - ICMC ; RIBAS, LUCAS CORREIA - ICMC
- Unidades: IFSC; ICMC
- DOI: 10.1007/978-3-030-30645-8_18
- Subjects: RECONHECIMENTO DE PADRÕES; REDES NEURAIS; VISÃO COMPUTACIONAL
- Keywords: Deep Convolutional Neural Networks; Texture analysis; Feature extraction
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: Springer
- Publisher place: Heidelberg
- Date published: 2019
- Source:
- Título do periódico: Lecture Notes in Computer Science - LNCS
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 11752, Part II, p. 192-202, 2019
- Conference titles: International Conference on Image Analysis and Processing- ICIAP
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
SCABINI, Leonardo Felipe dos Santos et al. Evaluating deep convolutional neural networks as texture feature extractors. Lecture Notes in Computer Science - LNCS. Heidelberg: Springer. Disponível em: https://doi.org/10.1007/978-3-030-30645-8_18. Acesso em: 19 abr. 2024. , 2019 -
APA
Scabini, L. F. dos S., Condori, R. H. M., Ribas, L. C., & Bruno, O. M. (2019). Evaluating deep convolutional neural networks as texture feature extractors. Lecture Notes in Computer Science - LNCS. Heidelberg: Springer. doi:10.1007/978-3-030-30645-8_18 -
NLM
Scabini LF dos S, Condori RHM, Ribas LC, Bruno OM. Evaluating deep convolutional neural networks as texture feature extractors [Internet]. Lecture Notes in Computer Science - LNCS. 2019 ; 11752 192-202.[citado 2024 abr. 19 ] Available from: https://doi.org/10.1007/978-3-030-30645-8_18 -
Vancouver
Scabini LF dos S, Condori RHM, Ribas LC, Bruno OM. Evaluating deep convolutional neural networks as texture feature extractors [Internet]. Lecture Notes in Computer Science - LNCS. 2019 ; 11752 192-202.[citado 2024 abr. 19 ] Available from: https://doi.org/10.1007/978-3-030-30645-8_18 - Color-texture classification based on spatio-spectral complex network representations
- Deep topological embedding with convolutional neural networks for complex network classification
- Fusion of complex networks and randomized neural networks for texture analysis
- Spatio-spectral networks for color-texture analysis
- A complex network approach for fish species recognition based on otolith shape
- Deep convolutional neural networks for plant species characterization based on leaf midrib
- Analysis of activation maps through global pooling measurements for texture classification
- Cellular automata rule characterization and classification using texture descriptors
- Complex texture features learned by applying randomized neural network on graphs
- IFSC/USP desenvolve “RADAM”: IA para padrões complexos - Primeira no mundo: Uma IA que treina outra IA. [Depoimento à Rui Sintra]
Informações sobre o DOI: 10.1007/978-3-030-30645-8_18 (Fonte: oaDOI API)
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