障碍物识别创新深度学习技术：现代检测算法的比较研究
计算机视觉与模式识别
2024-10-15 v1 机器人学
摘要
本研究探索了一种针对障碍物检测的综合方法，具体使用先进的YOLO模型，包括YOLOv8、YOLOv7、YOLOv6和YOLOv5。利用深度学习技术，该研究聚焦于这些模型在实际时延检测场景中的性能比较。研究结果表明，YOLOv8在提高精确召回率指标方面取得最高准确率。 presented detailed training processes, algorithmic principles, and a range of experimental results to validate the model's effectiveness.
引用
@article{arxiv.2410.10096,
title = {Innovative Deep Learning Techniques for Obstacle Recognition: A Comparative Study of Modern Detection Algorithms},
author = {Santiago Pérez and Camila Gómez and Matías Rodríguez},
journal= {arXiv preprint arXiv:2410.10096},
year = {2024}
}