Algorithms for Object Detection in Substations
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Abstract (arXiv)
Inspection of high-voltage power equipment is an effective way to ensure power supply reliability. Object recognition, one of the key technologies in automatic power equipment inspection, attracts attention of many researchers and engineers. Although quite a few existing models have some their own advantages, object relationship between equipment which is very important in this task is scarcely considered. This paper combining object relationship modeling and Transformer Model proposes a Relation Transformer Model. It has four parts -- backbone, encoder, decoder and prediction heads. With this structure, the proposed method shows in experiments a much better performance than other three commonly used models in object recognition in substation, largely promoting the development of automatic power equipment inspection.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 16 references that are in the map. First posted on arXiv 23 Sep 2023.
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References · 8
- 2017Attention Is All You Needcited by 60,361
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
- 2020End-to-End Object Detection with Transformerscited by 7,414
- 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
- 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,368
- 2018Image Transformercited by 772
- 2019Attention Augmented Convolutional Networkscited by 363
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