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Publishing Language: Chinese | Open Access

Application of artificial intelligence technology to trace evidence identification

Can HU( )Jun ZHUHongcheng MEIHongling GUOYajun LIXianhe DENGZhi LI
Institute of Forensic Science, Ministry of Public Security, Beijing 100038
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Abstract

Trace evidence identification is a vital aspect of forensic identification but is facing methodological challenges since the utilized analytical methods have slow processing speeds, limited accuracy, and a reliance on expert experience. Recently, artificial intelligence (AI) technologies have introduced innovative solutions for the recognition, analysis, and comparison of trace evidence, greatly enhancing both efficiency and accuracy, particularly machine learning, computer vision, and deep learning. This paper reviews the application of AI technology in the examination of trace evidence, including aspects such as spectral analysis, microscopic image analysis, and result interpretation. The roles of AI were discussed in respect of improving the efficiency and accuracy of forensic examinations, with some of its future development prospects.

CLC number: DF79; O65 Document code: A

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Journal of Capital Normal University (Natural Science Edition)
Pages 1-7

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Cite this article:
HU C, ZHU J, MEI H, et al. Application of artificial intelligence technology to trace evidence identification. Journal of Capital Normal University (Natural Science Edition), 2025, 46(5): 1-7. https://doi.org/10.19789/j.1004-9398.2025.05.001

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Received: 11 December 2024
Published: 01 October 2025
© The editorial department of Journal of Capital Normal University (Natural Science Edition) 2025.

This is an open access article under the CC BY-NC-ND 4.0 license (https://creativecommons.org/licenses/by-nc-nd/4.0/).