基于YOLOv8的目标检测算法改进研究OA
Research on the Improvement of Target Detection Algorithm Based on YOLOv8
现有的目标检测网络往往存在结构复杂、参数量巨大的问题.因此,研究结构简单、参数量少的高精度目标检测算法,其重要性和价值不言而喻.YOLO系列算法作为深度学习时代具有代表性的单阶段目标检测算法,具有准确、高效和易于部署等特点,为目标检测提供了非常好的理论及技术基础.因此,文章在YOLOv8 的基础上对其卷积网络进行改进,实验结果证明,改进算法成功提升了检测精度.
The existing target detection network often has the problems of complex structure and huge parameters.Therefore,it is difficult to study the high-precision target detection algorithm with simple structure and a few parameters.As a representative single-stage target detection algorithm in the era of Deep Learning,YOLO series algorithms have the characteristics of accuracy,high efficiency and easy deployment,which provides a very good theoretical and tec…查看全部>>
肖富坤
沈阳航空航天大学,辽宁 沈阳 110136
计算机与自动化
目标检测高精度YOLOv8卷积网络
target detectionhigh accuracyYOLOv8convolutional network
《现代信息科技》 2024 (18)
52-58,7
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