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昝露洋, 李柏鹏, 卢凯旋, 等. 基于Poly-FPN神经网络模型的化工厂智能检测[J/OL]. 遥感学报, 2021,null.
Intelligent Detection of Chemical Plants Based on Poly-FPN Neural Network[J/OL]. Journal of Remote Sensing, 2021,null.
Chemical plant safety accidents are frequent, the government has carried out a major crackdown on chemical enterprises. Compared with manual investigation with a small range and low efficiency, satellite remote sensing can efficiently monitor chemical plants in a large range, which is of great importance for production safety supervision and accident prevention in China"s chemical industry. Due to the irregular shape, strong semantic information and scattered distribution of chemical plants, the existing detection model has low precision and is difficult to be applied. In this paper, we proposed Poly-FPN object detection model, this model adopts the feature pyramid structure, improve the processing capacity of the complicated semantic target, at the same time through the proposed arbitrary quadrilateral detection head alternatives to the traditional rectangular head, realizing the objective of the irregular accurate detection. Finally, based on poly-fpn, a large area of the lower reaches of the Yangtze river was predicted, and the high-precision detection of chemical plants was realized.
深度学习 目标检测 卫星遥感 化工厂提取 任意四边形检测