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Representações intermediárias em Ciência Computacional para descoberta de conhecimento

Processo: 15/22308-2
Modalidade de apoio:Auxílio à Pesquisa - Temático
Vigência: 01 de novembro de 2017 - 31 de outubro de 2023
Área do conhecimento:Ciências Exatas e da Terra - Ciência da Computação - Metodologia e Técnicas da Computação
Pesquisador responsável:Roberto Marcondes Cesar Junior
Beneficiário:Roberto Marcondes Cesar Junior
Instituição Sede: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brasil
Pesquisadores principais:
Carlos Alberto Moreira Filho ; Luciano da Fontoura Costa ; Nina Sumiko Tomita Hirata ; Ronaldo Fumio Hashimoto
Pesquisadores associados:Cesar Henrique Comin ; Edson Amaro Junior ; Fernanda Bernardi Bertonha ; Marcel Parolin Jackowski ; Maria da Graca Campos Pimentel ; Roberto Hirata Junior ; Ronaldo Fumio Hashimoto ; Silvia Yumi Bando Takahara ; Valeria Meirelles Carril Elui
Auxílios(s) vinculado(s):20/06160-3 - Resposta transcricional de leucócitos humanos à infecção por SARS-CoV-2, AP.R
18/17421-2 - 2018 IEEE International Conference on Image Processing, AR.EXT
Bolsa(s) vinculada(s):23/02619-0 - Redes neurais convolucionais e transformers visuais aplicados à detecção de doenças em imagens de folhas de plantas, BP.IC
22/14286-2 - Classificação de espécies de aranha utilizando Transformers Visuais e Redes Convolucionais, BP.IC
22/12204-9 - Desenvolvimento de métodos para descrição de imagens: um arcabouço baseado em visão computacional e processamento de linguagem natural, BP.PD
+ mais bolsas vinculadas 22/10478-4 - Administrador da Cyberinfraestrutura do Projeto, BP.TT
22/11645-1 - Classificação de estrelas, galáxias e quasares baseada em imagens fotométricas multibandas, BP.IC
21/07112-5 - Modelando o conhecimento por redes complexas, BP.IC
21/09070-8 - Modelagem, análise e inferência de redes biológicas, BP.PD
20/13255-0 - Algoritmos para aquisição, formação e anotação de imagens de sensoriamento remoto, BP.TT
20/13275-1 - Administrador da cyberinfraestrutura do projeto, BP.TT
20/06744-5 - Deep learning e representações intermediárias para análise de imagens pediátricas, BP.PD
19/23343-7 - Análise temporal da expressão gênica, BP.PD
19/01077-3 - Integrando imagens e redes complexas na análise de cidades, BP.PD
19/06280-1 - Integração, transformação, aumento de dados e controle de qualidade para representações intermediárias, BP.PD
19/06254-0 - Reconhecimento estrutural de padrões e representações intermediárias, BP.PD
19/04219-3 - Administrador da cyberinfraestrutura do projeto, BP.TT
18/10489-0 - Transformações de redes complexas e suas implicações na topologia e dinâmica de sistemas complexos, BP.PD
18/00390-7 - Detecção de códigos QR usando modelos de aprendizado profundo, BP.MS
18/00477-5 - Aprendizado de transformações imagem-a-imagem, BP.MS
18/07386-5 - Segmentação de imagens de ressonância magnética neonatal: uma abordagem estrutural, BP.MS - menos bolsas vinculadas
Assunto(s):Visão computacional  Aprendizado computacional  Processamento de imagens  Biologia de sistemas  Reconhecimento de padrões 
Palavra(s)-Chave do Pesquisador:Aprendizado de Máquina | biologia de sistemas | eScience | Processamento de imagens | Reconhecimento de Padrões | Visão Computacional | Reconhecimento de padrões

Resumo

Este projeto centra-se em uma estratégia unificada para descoberta de conhecimento e dinâmicas emergentes em Ciência Computacional usando representações intermediárias. As aplicações pretendidas estão em áreas caracterizadas por extrema abundância de dados, nas quais a descoberta de conhecimento implica na transição das bases de dados brutos para representações intermediárias, usualmente vetores de características e grafos, permitindo assim o emprego subsequente de diferentes métodos analíticos. Nesse contexto, os métodos de integração e transformação a serem utilizados na geração dos dados intermediários também devem garantir a qualidade e confiabilidade dos dados gerados para a representação intermediária. Os resultados da fase de análise podem influenciar tanto os métodos de integração como experimentos para nova geração de dados através de mecanismos de feedback. O presente projeto possui dois objetivos gerais: 1) desenvolver métodos originais para resolver problemas de Ciência Computacional baseadas em uma abordagem comum de representações intermediárias; 2) aplicar os métodos desenvolvidos em problemas específicos. Essa estratégia metodológica será empregada para abordar problemas específicos em áreas de fronteira da Ciência, nos quais nosso grupo tem trabalhado nos últimos anos: representações intermediárias em visão computacional e informática urbana; estudo dinâmico de redes biológicas para caracterizar os mecanismos de transição saúde-doença; desenvolvimento de ferramentas computacionais para processamento de imagens de MRI de alto campo e sua integração com dados biológicos; desenvolvimento de novas técnicas para caracterização e visualização de representações intermediárias em redes complexas dinâmicas, com aplicações em Biologia de Sistemas. (AU)

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Publicações científicas (133)
(Referências obtidas automaticamente do Web of Science e do SciELO, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores)
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ALMEIDA DE MACEDO OLIVEIRA, ARTUR ANDRE; HIRATA JR, ROBERTO. INACITY - INvestigate and Analyze a CITY. SOFTWAREX, v. 15, . (18/10767-0, 15/22308-2, 15/24485-9)
TOKUDA, ERIC K.; DE ARRUDA, HENRIQUE F.; COMIN, CESAR H.; JR, ROBERTO M. CESAR; SILVA, CLAUDIO T.; COSTA, LUCIANO DA F.. Spatial distribution of graffiti types: a complex network approach. European Physical Journal B, v. 94, n. 9, . (19/01077-3, 19/16223-5, 18/09125-4, 15/22308-2, 18/10489-0)
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RIBEIRO PRIST, PAULA; REVERBERI TAMBOSI, LEANDRO; FILIPE MUCCI, LUIS; PINTER, ADRIANO; PEREIRA DE SOUZA, RENATO; DE LARA MUYLAERT, RENATA; ROGER RHODES, JONATHAN; HENRIQUE COMIN, CESAR; DA FONTOURA COSTA, LUCIANDO; LANG D'AGOSTINI, TATIANA; et al. Roads and forest edges facilitate yellow fever virus dispersion. JOURNAL OF APPLIED ECOLOGY, v. 59, n. 1, . (18/09125-4, 18/14389-0, 15/22308-2, 18/23364-1, 17/11666-0)
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DAMINELI, DANIEL S. C.; PORTES, MARIA TERESA; FEIJO, JOSE A.. Electrifying rhythms in plant cells. CURRENT OPINION IN CELL BIOLOGY, v. 77, p. 11-pg., . (19/23343-7, 21/05363-0, 19/26129-6, 15/22308-2)
BRITO, ANA C. M.; SILVA, FILIPI N.; DE ARRUDA, HENRIQUE F.; COMIN, CESAR H.; AMANCIO, DIEGO R.; COSTA, LUCIANO DA F.. Classification of abrupt changes along viewing profiles of scientific articles. Journal of Informetrics, v. 15, n. 2, p. 15-pg., . (18/09125-4, 18/10489-0, 15/22308-2, 16/19069-9, 15/08003-4)
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MONTEIRO, BRUNO A. A.; OLIVEIRA, HUGO; DOS SANTOS, JEFERSSON A.. Self-Supervised Learning for Seismic Image Segmentation From Few-Labeled Samples. IEEE Geoscience and Remote Sensing Letters, v. 19, p. 5-pg., . (20/06744-5, 15/22308-2)
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DINIZ, PAULO S. R.; YAZDANPANAH, NAMED; LIMA, MARKUS V. S.; IEEE. Feature LMS Algorithm for Bandpass System Models. 2019 27TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), v. N/A, p. 5-pg., . (19/06280-1, 15/22308-2)
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CARVALHO, THIAGO; MARTINEZ, JORGE A. CHAMORRO; OLIVEIRA, HUGO; DOS SANTOS, JEFERSSON A.; FEITOSA, RAUL QUEIROZ. Outlier Exposure for Open Set Crop Recognition From Multitemporal Image Sequences. IEEE Geoscience and Remote Sensing Letters, v. 20, p. 5-pg., . (20/06744-5, 15/22308-2)
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