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Detection of Self-Build Data Set Based on YOLOv4 Network

机译:基于YOLOv4网络的自建数据集检测

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摘要

To improve the anti-ship missiles' ability for accurate and efficient detection of maritime targets, YOLOv4 detection network is used in this paper. By using YOLOv4 network to detect the self-built marine ship targets' data set, to verify the accuracy and speed of the ship's recognition of the network. Empirical results show that YOLOv4 network can achieve better detection results for single or multiple targets in the pictures, and had superior performance in detecting small and obscure targets. In the real-time detection link, it can quickly and accurately detect the ship target in the transformed scene. Compared with traditional marine ship targets detection methods, YOLOv4 can better avoid the influence of background, lighting, occlusion, etc. It provides the oretical and technical support for the fine selection of targets for anti-ship missiles.
机译:为了提高反舰导弹对海上目标的精确有效检测能力,本文采用了YOLOv4检测网络。通过使用YOLOv4网络检测自建海上目标的数据集,以验证船舶识别网络的准确性和速度。实验结果表明,YOLOv4网络可以对图片中的单个或多个目标获得更好的检测结果,并且在检测小的和模糊的目标方面具有优越的性能。在实时检测链接中,它可以快速,准确地检测到变换场景中的船只目标。与传统的海上舰船目标检测方法相比,YOLOv4可以更好地避免背景,光线,遮挡等因素的影响。为精细选择反舰导弹目标提供了理论和技术支持。

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