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03 - CONFIGURAÇÃO DO AMBIENTE DE DESENVOLVIMENTO, PADRÃO DE DATASET E TREINAMENTO PARA YOLO

Doi: 10.47094/978-65-284-0683-8/43-56

PALAVRAS CHAVE: Inteligência artificial - Aplicações médicas. Redes neurais (Ciência da computação) - Aplicações médicas. Sistemas de detecção de objetos (YOLO).

KEYWORDS: Artificial intelligence - Medical applications. Neural networks (Computer science) - Medical applications. Object detection systems (YOLO).

ABSTRACT:
1. INTRODUCTION AND PREPARATION OF THE INTERACTIVE ENVIRONMENT
Training detectors from the YOLO (You Only Look Once) family requires a software environment compatible with the available graphics accelerators. In workflows using Jupyter Notebooks or local scripts, the Ultralytics package, the Pandas library, and PyTorch—compiled with support for CUDA and cuDNN—are employed. The following sections cover the installation of these dependencies, the standardization of the dataset, and the training parameters for YOLOv12.

Autores

  • Adriano Carvalho Costa

  • Adriano Soares de Oliveira Bailão

  • Andrea Barboza Proto Sardi

  • Gabriela Almeida Marques

  • Gidelia Araújo Ferreira de Melo

  • Gustavo Henrique Joazeiro de Almeida

  • Juliana Fortunato

  • Leandro Manuel Pereira Sanches

  • Lorena Santana Arantes

  • Matheus Barp Pierozan

  • Ronaldo Camilo dos Santos

  • Sergio Souza Novak

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