Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
基于机器学习的人体气味识别及其在法庭科学领域的应用. (Chinese) |
| Alternate Title: |
Machine Learning-based Human Odor Recognition and Application in Forensic Science. (English) |
| Συγγραφείς: |
张宇, 任昕昕, 宋歌, 董林沛, 李佳宜, 胡晓光 |
| Πηγή: |
Forensic Science & Technology; Oct2025, Vol. 50 Issue 5, p529-536, 8p |
| Θεματικοί όροι: |
Machine learning, Body odor, Forensic sciences, Electronic data processing, University research, Biomarkers, Recognition (Psychology) |
| Abstract (English): |
Human body odor arises from the secretion of various glands on the skin's surface, which, when acted upon by microorganisms, evaporate to produce a distinct scent. This odor contains valuable biological information, with certain compounds exhibiting strong stability and individual specificity, serving as "odor fingerprinting" that can distinguish between different populations. Machine learning is an important method for human odor research, which can not only explore the characteristic components of odor in different populations, but also investigate the differences between different individuals. This paper discusses the application of "odor fingerprinting" in individual identification and feature characterization, drawing upon recent literature. It outlines the data processing procedures involved in human odor analysis, highlights the challenges encountered, and explores current research trends. Finally, the application trends of the recognition of human odor are discussed in order to provide reference for odor recognition research. [ABSTRACT FROM AUTHOR] |
| Abstract (Chinese): |
人体气味是人体多种腺体的分泌物在皮肤表面微生物的作用下挥发形成的气味, 包含大量生物信息, 其中部分化合物具有较强的稳定性以及个体特异性, 可以作为不同人体特征识别的 "气纹特征" 。机器学习是 人体气味研究的重要方法, 不仅可以探究不同人群气味中的特征组分, 还可以考察不同个体之间差异性。本文 参考近几年文献, 总结了基于机器学习的人体气味数据处理流程, 讨论了 "气纹特征" 在个体识别和特征刻画 中的应用, 以及在数据分析过程中的难点以及研究趋势, 对人体气味的识别做出展望, 以期为此类研究提供参考. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
Biomedical Index |