Use este identificador para citar ou linkar para este item:
http://www.repositorio.ufop.br/jspui/handle/123456789/10837
Título: | Reverse image search for scientific data within and beyond the visible spectrum. |
Autor(es): | Araujo, Flavio Henrique Duarte de Silva, Romuere Rodrigues Veloso e Medeiros, Fátima Nelsizeuma Sombra de Parkinson, Dilworth Dula Hexemer, Alexander Carneiro, Cláudia Martins Ushizima, Daniela Mayumi |
Palavras-chave: | Content-based image retrieval Convolutional neural network Scientific image recommendation |
Data do documento: | 2018 |
Referência: | ARAUJO, F. H. D. de et al. Reverse image search for scientific data within and beyond the visible spectrum. Expert Systems with Applications, v. 109, p. 35-48, nov. 2018. Disponível em: <https://www.sciencedirect.com/science/article/pii/S0957417418302987>. Acesso em: 21 fev. 2019. |
Resumo: | The explosion in the rate, quality and diversity of image acquisition instruments has propelled the de- velopment of expert systems to organize and query image collections more efficiently. Recommendation systems that handle scientific images are rare, particularly if records lack metadata. This paper intro- duces new strategies to enable fast searches and image ranking from large pictorial datasets with or without labels. The main contribution is the development of pyCBIR , a deep neural network software to search scientific images by content. This tool exploits convolutional layers with locality sensitivity hashing for querying images across domains through a user-friendly interface. Our results report image searches over databases ranging from thousands to millions of samples. We test pyCBIR search capabilities using three convNets against four scientific datasets, including samples from cell microscopy, microtomography, atomic diffraction patterns, and materials photographs to demonstrate 95% accurate recommendations in most cases. Furthermore, all scientific data collections are released. |
URI: | http://www.repositorio.ufop.br/handle/123456789/10837 |
Link para o artigo: | https://www.sciencedirect.com/science/article/pii/S0957417418302987?via%3Dihub#! |
ISSN: | 09574174 |
Aparece nas coleções: | DEACL - Artigos publicados em periódicos |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
---|---|---|---|---|
ARTIGO_ReverseImageSearch.pdf Restricted Access | 6,37 MB | Adobe PDF | Visualizar/Abrir |
Os itens no repositório estão protegidos por copyright, com todos os direitos reservados, salvo quando é indicado o contrário.