Remote sensing image ship detection method and device based on attention model

An attention model and remote sensing image technology, applied in the field of target detection and computer vision, can solve problems such as difficult to effectively extract detailed information, achieve significant application value, improve detection rate, and improve quality

Pending Publication Date: 2022-06-28
ZHEJIANG LAB +1
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Problems solved by technology

However, in remote sensing images, ship targets are mostly extremely small targets, and it is difficult to effectively extract rich detailed

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  • Remote sensing image ship detection method and device based on attention model
  • Remote sensing image ship detection method and device based on attention model
  • Remote sensing image ship detection method and device based on attention model

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[0029] In order to make the objectives, technical solutions and technical effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments of the description.

[0030] like figure 1 and figure 2 As shown, the remote sensing image ship detection method based on small sample data enhancement and attention model of the present invention includes the following steps:

[0031] Step 1: Collect remote sensing images of ships, and use annotation information to expand the remote sensing image dataset;

[0032] Specifically, the remote sensing images of ships are collected, the bounding boxes and outlines of ships in the images are marked by the ship labeling method, the labeling information of the ship outlines is obtained, the corresponding ship pictures are cut out to form a ship picture library, and the pictures in the ship picture library are randomly selected. Select several ima...

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Abstract

The invention discloses a remote sensing image ship detection method and device based on an attention model, and the method comprises the steps: 1, collecting a ship remote sensing image, and carrying out the data expansion of an image data set through annotation information; step 2, preprocessing the collected remote sensing image to obtain a data set used for ship detection model training; 3, inputting the images in the training data set into a YOLOV5 attention model improved for a small-size target, and training to obtain a trained remote sensing ship detection model; 4, cutting a remote sensing image to be detected, inputting the cut remote sensing image into the trained remote sensing ship detection model, and outputting a bounding box and confidence of a ship; and mapping bounding boxes of all the cut images back to the original remote sensing image, and obtaining a final detection result after filtering repeated targets through confidence threshold filtering and non-maximum suppression. According to the invention, the problem of difficult detection caused by sparse ship distribution and too small size in the remote sensing image is solved.

Description

technical field [0001] The invention belongs to the fields of computer vision and target detection, and in particular relates to a remote sensing image ship detection method and device based on an attention model. Background technique [0002] In recent years, with the continuous development of intelligent science and technology, and the increasing strategic status of the ocean, in order to improve the ability to supervise and control the ocean, countries have gradually increased the research on ocean monitoring. As an important tool in marine transportation, the positioning of ships in key sea areas is of great significance in the fields of national defense and trade. Since most of the scenes detected and identified by ships are in the vast sea, images are usually collected by means of remote sensing satellites or drones. However, in remote sensing or aerial photography scenarios, the collected images usually have problems such as too small ship targets, sparse distributio...

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Application Information

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IPC IPC(8): G06V20/10G06V20/54G06V10/774G06V10/82G06V10/26G06V10/44G06N3/04G06N3/08G06K9/62
CPCG06N3/08G06N3/045G06F18/214
Inventor 黎晨阳王军徐晓刚徐冠雷朱亚光
Owner ZHEJIANG LAB
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