卷积神经网络在物证检验中的应用与毛发自动识别的展望

随着近年来人工智能的迅速发展,机器学习在各领域的应用愈发广泛。对卷积神经网络及其近年来在物证检验领域取得的研究成果与进展进行综述;同时对其在毛发物证检验中的应用进行设想与展望。首先介绍卷积神经网络的结构与基本原理;其次对卷积神经网络的优缺点进行了总结,对卷积神经网络在人脸识别、笔迹识别、音频识别、步态识别等领域的应用与发展历程进行了综述;最后阐述了目前对于卷积神经网络应用于物证检验领域中毛发的无损检验这一新领域进行可行性分析。

Application of Convolutional Neural Network in Forensic Evidence Examination and Prospect of Hair Evidence Identification

With the rapid development of artificial intelligence in recent years, the application of machine learning in various fields has become more and more extensive. In this paper, the convolutional neural network and its research achievements and progress in the field of forensic evidence examination are reviewed, and its application in hair evidence examination is envisioned and prospected. Firstly, the structure and basic principles of convolutional neural networks are introduced. Secondly, the advantages and disadvantages of convolutional neural networks are summarized. The application and development of convolutional neural networks in face recognition, handwriting recognition, audio recognition and gait recognition are introduced. Finally, the feasibility analysis of non-destructive hair evidence examination by convolutional neural networks is presented.