| Texto completo | |
| Autor(es): |
Sa, Jarbas Joaci de Mesquita, Jr.
;
Backes, Andre R.
;
Bruno, Odemir Martinez
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2017; v. 10657, p. 8-pg., 2018-01-01. |
| Resumo | |
This paper presents a state-of-the-art texture analysis method called "randomized neural network based signature" applied to the classification of pap-smear cell images for the Papanicolaou test. For this purpose, we used a well-known benchmark dataset composed of 917 images and compared the aforementioned image signature to other texture analysis methods. The obtained results were promising, presenting accuracy of 87.57% and AUC of 0.8983 using LDA and SVM, respectively. These performance values confirm that the randomized neural network based signature can be applied successfully to this important medical problem. (AU) | |
| Processo FAPESP: | 14/08026-1 - Visão artificial e reconhecimento de padrões aplicados em plasticidade vegetal |
| Beneficiário: | Odemir Martinez Bruno |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |