Abstract

Remote sensing target detection has been widely used in industries. In various application scenarios, complicated contexts may inhibit target identification and reduce detection accuracy, especially in multi-target detection tasks. In this paper, a new remote sensing target detection method based on structural reasoning is proposed to improve target detection performance by integrating inter-object relationships and scene information. Based on inter-object information, a relation structure graph is designed to reduce errors and missed targets. To establish contextual constraints, semantic is used as a prior information for Bayesian criterion based on scene information. Experiments conducted on HRRSD dataset show that the average accuracy of the proposed method is 10.7

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Cite this article

@article{cai-6406,
  author  = {Yi Ding and Xiangru Lyu and Liuyang Yan and Lan Rong and Keyang Cheng},
  title   = {Remote Sensing Target Detection Inspired by Scene Information and Inter-Object Relations},
  journal = {Computing and Informatics},
  volume  = {42},
  number  = {6},
  pages   = {1404--1427},
  year    = {2023},
  issn    = {1335-9150},
  doi     = {10.31577/cai_2023_6_1404}
}
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