Multi-scale large well building object detection based on deep learning

doi:10.7523/j.issn.2095-6134.2021.06.010

Abstract

Abstract: Large well building is important remote sensing object, and the research on object detection of large well buildings is of great significance to national defense. At the data level, due to the small number of large well buildings samples, there is currently no valid data set available for the object detection. Building effective datasets is of great value for the research in related fields. At the algorithm level,the different resolutions of the remote sensing images result in multi-scale characteristics of the large well buildings, which is one of the difficulties in solving the object detection problem. Based on the above analysis, firstly, this article built the first large well buildings object detection dataset using Google Earth. Then an effective detection model was designed for large well building object detection task. The model in this paper fully integrates the object's multi-scale features and contextual information, and detects the object through the multi-stage cascade network. The model can effectively detect large well buildings, and the detection effect is better than the results of the current mainstream algorithms.

Key words: large well building, multi-scale, feature fusion, contextual information

CLC Number:

TP751.2

MENG Xiting, JI Luyan, ZHAO Yongchao, YANG Weitun. Multi-scale large well building object detection based on deep learning[J]. Journal of University of Chinese Academy of Sciences, 2021, 38(6): 800-808.

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