A web-based system to assess texture analysis methods and datasets (2019)
- Authors:
- USP affiliated authors: BRUNO, ODEMIR MARTINEZ - IFSC ; FARFAN, ALEX JOSUE FLOREZ - ICMC ; SCABINI, LEONARDO FELIPE DOS SANTOS - IFSC
- Unidades: IFSC; ICMC
- DOI: 10.1007/978-3-030-29891-3_37
- Subjects: RECONHECIMENTO DE PADRÕES; REDES NEURAIS; VISÃO COMPUTACIONAL
- Keywords: Texture classification; Feature extraction; Web-based application
- 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. 11679, Part II, p. 425-437, 2019
- Conference titles: International Conference on Computer Analysis of Images and Patterns - CAIP
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
FARFAN, Alex Josue Florez e SCABINI, Leonardo Felipe dos Santos e BRUNO, Odemir Martinez. A web-based system to assess texture analysis methods and datasets. Lecture Notes in Computer Science - LNCS. Heidelberg: Springer. Disponível em: https://doi.org/10.1007/978-3-030-29891-3_37. Acesso em: 19 set. 2024. , 2019 -
APA
Farfan, A. J. F., Scabini, L. F. dos S., & Bruno, O. M. (2019). A web-based system to assess texture analysis methods and datasets. Lecture Notes in Computer Science - LNCS. Heidelberg: Springer. doi:10.1007/978-3-030-29891-3_37 -
NLM
Farfan AJF, Scabini LF dos S, Bruno OM. A web-based system to assess texture analysis methods and datasets [Internet]. Lecture Notes in Computer Science - LNCS. 2019 ; 11679 425-437.[citado 2024 set. 19 ] Available from: https://doi.org/10.1007/978-3-030-29891-3_37 -
Vancouver
Farfan AJF, Scabini LF dos S, Bruno OM. A web-based system to assess texture analysis methods and datasets [Internet]. Lecture Notes in Computer Science - LNCS. 2019 ; 11679 425-437.[citado 2024 set. 19 ] Available from: https://doi.org/10.1007/978-3-030-29891-3_37 - Artificial neural networks and complex networks: an integrative study of topological properties and pattern recognition
- Local complex features learned by randomized neural networks for texture analysis
- Improving deep neural network random initialization through neuronal rewiring
- Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning
- IFSC/USP desenvolve “RADAM”: IA para padrões complexos - Primeira no mundo: Uma IA que treina outra IA. [Depoimento à Rui Sintra]
- Structure and functioning of neural networks: the complex network properties of artificial neurons
- Artificial neural networks and complex networks: an integrative study of topological properties and pattern recognition
- IA desenvolvida na USP é a melhor do mundo para reconhecer texturas [Depoimento a Ivan Conterno]
- Environment for the analysis and comparison of texture descriptors
- Social interaction layers in complex networks for the dynamical epidemic modeling of COVID-19 in Brazil
Informações sobre o DOI: 10.1007/978-3-030-29891-3_37 (Fonte: oaDOI API)
Download do texto completo
Tipo | Nome | Link | |
---|---|---|---|
PROD029080_2960406.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas