基于YOLO算法的绝缘子和减振器图像处理

Chinzorig Sunduijav, W. Hardt, Zagdkhorol Bayasgalan
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引用次数: 2

摘要

图像处理广泛应用于许多领域,包括电子、计算机科学、能源、建筑、医学和自动驾驶汽车。基于深度学习的目标检测方法也发展到实时检测。根据要处理的对象或图像的性质,图像处理方法的性能将因应用程序而异。因此,研究人员在每种情况下测试不同类型的算法,并比较性能结果。这项研究的目的是检测和报告选定的物体,如绝缘体和减振器。这段视频是用无人机在输电线上拍摄的。本研究旨在通过图像处理后的输入数据对绝缘子进行识别,建立图像数据库,然后报告可见的物理损伤。本研究总结了一项研究的结果,其中视频绝缘体和减振器检测使用DL你只看一次算法。
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Image Processing of Insulator and Vibration Damper by YOLO Algorithm
Image processing is widely used in many fields, including electronics, computer science, energy, construction, medicine, and self-driving cars. Deep learning based object detection methods have also evolved to detect in real-time. Depending on the nature of the object or image to be processed, the performance of image processing methods will vary from application to application. Therefore, researchers test different types of algorithms in each case and compare performance results. The study aims to detect and report selected objects, such as insulators and vibration dampers. This video was recorded by using an UAV in a power transmission line. The research aims to identify the insulator from the input data processed by image processing, create an image database, and then report the visible physical damages. This study summarizes the results of a study in which video insulators and vibration dampers were detected using the DL youonly look once algorithm.
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