Source: Proceedings of SPIE. Conference titles: Photonics West. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL, CÉLULAS
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GARCIA, Marlon Rodrigues et al. White blood cells segmentation and classification using a random forest and residual networks implementation. Proceedings of SPIE. Bellingham: International Society for Optical Engineering - SPIE. Disponível em: https://repositorio.usp.br/directbitstream/e74c64bc-3ce8-4b09-8092-d10cdfe4170f/PROD035697_3186763.pdf. Acesso em: 17 nov. 2024. , 2024APA
Garcia, M. R., Ayala, E. T. P., Pratavieira, S., & Bagnato, V. S. (2024). White blood cells segmentation and classification using a random forest and residual networks implementation. Proceedings of SPIE. Bellingham: International Society for Optical Engineering - SPIE. doi:10.1117/12.3007504NLM
Garcia MR, Ayala ETP, Pratavieira S, Bagnato VS. White blood cells segmentation and classification using a random forest and residual networks implementation [Internet]. Proceedings of SPIE. 2024 ; 12857[citado 2024 nov. 17 ] Available from: https://repositorio.usp.br/directbitstream/e74c64bc-3ce8-4b09-8092-d10cdfe4170f/PROD035697_3186763.pdfVancouver
Garcia MR, Ayala ETP, Pratavieira S, Bagnato VS. White blood cells segmentation and classification using a random forest and residual networks implementation [Internet]. Proceedings of SPIE. 2024 ; 12857[citado 2024 nov. 17 ] Available from: https://repositorio.usp.br/directbitstream/e74c64bc-3ce8-4b09-8092-d10cdfe4170f/PROD035697_3186763.pdf