Insulator String Detection Method Based on the InST-Net Network

Zhuo Haoze, Han Jiaming, Zhou Guoxing, Yang Zhong and Muhammad Faisal Nadeem

Mathematical Problems in Engineering, 2022, vol. 2022, 1-7

Abstract: Aiming at the problem of detecting insulator strings in aerial images, a detection method of insulator strings based on the InST-Net network is proposed in this paper. First, the ResNet50 network pretrained on the ImageNet dataset is used as the backbone network for insulator string feature extraction. Subsequently, for insulator strings of different imaging sizes in the image, three detection branches are designed based on the design ideas of the existing YOLO model. Finally, an SPP module is adopted to improve the feature extraction capability of each detection branch of the proposed InST-Net network. The experimental results show that the InST-Net network detection accuracy rate reaches 90.63%, which is higher than that of the four classic one-stage target detection networks and the existing insulator string detection network.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:4037131

DOI: 10.1155/2022/4037131

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