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A target detection method, device and storage medium

A target detection and target technology, applied in the field of target detection, can solve the problem that the accuracy cannot meet the detection requirements, and achieve the effect of improving the accuracy

Active Publication Date: 2021-06-29
DEEPBLUE TECH (SHANGHAI) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The embodiment of the application provides a target detection method, device and storage medium to solve the problem in the prior art that the accuracy of target detection using faster rcnn cannot meet the detection requirements

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  • A target detection method, device and storage medium
  • A target detection method, device and storage medium
  • A target detection method, device and storage medium

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Embodiment Construction

[0029] In order to solve the problem in the prior art that the accuracy of target detection using faster rcnn cannot meet the detection requirements, the embodiments of the present application provide a target detection method, device and storage medium. In order to better understand the technical solution provided by the embodiment of the present application, here is a brief description of the basic principle of the solution:

[0030] By performing a collection operation on the candidate frames of the RPN layer in multiple faster rcnn, the collected candidate frames are obtained, and the collected candidate frames are input into the ROI pooling layer. The set operation is performed again on the output frame output by the ROI pooling layer to obtain the final output result. In this way, by performing set operations on the RPN layer and the ROI pooling layer respectively, more candidate boxes and output boxes can be obtained, thereby improving the accuracy of target detection u...

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Abstract

The application discloses a target detection method, device and storage medium, which relate to the field of target detection and are used to solve the problem in the prior art that the accuracy of target detection using the faster rcnn model cannot meet the detection requirements. The method includes: performing an ensemble operation on the candidate frames of the RPN layer in multiple faster rcnns, and inputting the assembled candidate frames into the ROI pooling layer. The set operation is performed again on the output frame output by the ROI pooling layer to obtain the final output result. In this way, by performing set operations on the RPN layer and the ROI pooling layer respectively, more candidate boxes and output boxes can be obtained, thereby improving the accuracy of target detection using faster rcnn.

Description

technical field [0001] The present application relates to the field of target detection, in particular to a target detection method, device and storage medium. Background technique [0002] Target detection, also called target extraction, is an image segmentation based on target geometric and statistical features. It combines target segmentation and recognition into one. Its accuracy and real-time performance are an important capability of the entire system. Especially in complex scenes, when multiple targets need to be processed in real time, automatic target extraction and recognition is particularly important. [0003] In order to achieve target detection, faster rcnn (faster Regions with Convolutional Neural Network, faster region nomination convolutional network) can be used for target detection on the image to be detected. However, in the prior art, the accuracy of target detection using faster rcnn cannot meet the detection requirements. Contents of the invention ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/11
Inventor 陈海波
Owner DEEPBLUE TECH (SHANGHAI) CO LTD