Accurate Target Positioning and Detection Algorithm Integrating Deep Learning and Prior Knowledge

Target targeting and detection is one of the core tasks in the field of computer vision, which has great significance for autonomous driving, intelligent surveillance, medical image analysis and other fields. In this paper, we propose an accurate target positioning and detection algorithm integrating deep learning and prior knowledge, aiming to combine the high efficiency of Faster R-CNN algorithm and the accuracy of prior knowledge to improve the accuracy and efficiency of target detection. Experimental results show that the proposed method achieves excellent performance on several datasets.

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Publication Details

Journal
Applied and Computational Engineering
Published
2024-11-26
DOI
https://doi.org/10.54254/2755-2721/2024.17891
Primary Topic
Infrared Target Detection Methodologies
Type
article
Field-Weighted Citation Impact
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article

Accurate Target Positioning and Detection Algorithm Integrating Deep Learning and Prior Knowledge

Ye Liu, Haisheng Song
Applied and Computational Engineering
Infrared Target Detection Methodologies
article

Accurate Target Positioning and Detection Algorithm Integrating Deep Learning and Prior Knowledge

Ye Liu, Haisheng Song
article en

Abstract

Target targeting and detection is one of the core tasks in the field of computer vision, which has great significance for autonomous driving, intelligent surveillance, medical image analysis and other fields. In this paper, we propose an accurate target positioning and detection algorithm integrating deep learning and prior knowledge, aiming to combine the high efficiency of Faster R-CNN algorithm and the accuracy of prior knowledge to improve the accuracy and efficiency of target detection. Experimental results show that the proposed method achieves excellent performance on several datasets.

Applied and Computational EngineeringVol. 109(1)
Northwest Normal University (CN)
Openalex Percentile: Top 66%
Infrared Target Detection Methodologies
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