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Ship Detection Method Based on Gabor Filter and Fast RCNN Model in Satellite Images of Sea

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Published:22 October 2019Publication History

ABSTRACT

In this paper, we design a new approach which combines the Gabor filter with the principle of selective search algorithm applied in Fast RCNN to extract and enhance the texture of the satellite image, to solve the problems of low detection precision, high probability of missed detection and error detection of ships in satellite images. Experiments show that the texture enhancement method based on Gabor filter fits the principle of selective search algorithm, which increases the number of positive samples in region proposal. The mAP of ship detection in satellite images reached 75.21%. And the detection accuracy of moving ships increased by 10%.

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  1. Ship Detection Method Based on Gabor Filter and Fast RCNN Model in Satellite Images of Sea

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    • Published in

      cover image ACM Other conferences
      CSAE '19: Proceedings of the 3rd International Conference on Computer Science and Application Engineering
      October 2019
      942 pages
      ISBN:9781450362948
      DOI:10.1145/3331453

      Copyright © 2019 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 22 October 2019

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      Overall Acceptance Rate368of770submissions,48%

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