使用YOLOX目标检测的经济高效的倒下树木识别解决方案

IF 0.3 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Hearim Moon, Juyeong Lee, Doyoon Kim, Eunsik Park, Junghyun Moon, Minsun Lee, Eric T. Matson, Minji Lee
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引用次数: 0

摘要

热带气旋是世界上最致命的自然灾害,特别是通过拔根或折断树木造成树木死亡,这对森林生态系统和森林所有者产生了很大的影响。为了尽量减少额外的损失,需要一种有效的方法来快速掌握倒下树木的位置和分布信息。过去有几项研究试图检测倒下的树木,但大多数研究需要巨大的成本,而且很难利用。本研究的重点是解决这些问题。无人机(UAV)被广泛用于地面探测,以满足在追求高分辨率图像的同时需要一种经济有效的方法。为了利用这一优势,本研究主要使用带有辅助高分辨率摄像头的无人机收集数据。收集到的数据用于训练YOLOX模型,这是一种目标检测算法,可以在非常短的时间内完成准确的检测。此外,通过使用YOLOX作为检测模型,获得了广泛的通用性,这意味着本研究驱动的解决方案可以用于任何需要廉价但高度可靠的目标检测结果的场景。本研究实现了一个可视化应用程序,该应用程序以客户友好的方式显示由训练模型计算的检测结果。倒下的树木在图像或视频中被识别出来,分析结果以基于网络的可视化形式提供。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cost-Effective Solution for Fallen Tree Recognition Using YOLOX Object Detection
Tropical cyclones are the world’s deadliest natural disasters, especially causing tree death by pulling out or breaking the roots of trees, which has a great impact on the forest ecosystem and forest owners. To minimize additional damage, an efficient approach is needed to quickly grasp information on the location and distribution of fallen trees. There are several studies that try to detect fallen trees in the past, but most of the research requires huge costs and is difficult to utilize. This research focuses on resolving those problems. Unmanned aerial vehicle (UAV) is widely used for ground detection for those who need a cost-effective way while pursuing high-resolution images. To take this advantage, this research collects data mainly using a UAV with an auxiliary high-resolution camera. The collected data is used for training the YOLOX model, an object detection algorithm, which can perform an accurate detection within a remarkably short time period. Also, by using YOLOX as a detection model, a wide-range versatility is obtained, which means, the solution driven by this research can be utilized for every scenario where inexpensive, but highly reliable object detection result is needed. This research implements a visualization application that displays detection results, calculated by a trained model, in a client-friendly way. Fallen trees are recognized in images or videos, and the analyzed results are provided as web-based visualizations.
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来源期刊
International Journal of Semantic Computing
International Journal of Semantic Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.70
自引率
12.50%
发文量
39
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