Efficient bi-traits identification using CEDRNN classifier for forensic applications

作者：

Highlights：

• Several operations are handled for bi-traits-centered offender identification.

• Image quality is highly increased by the proposed method of offender identification.

• The system solves the computation issues of tree structure part model.

• A new way is used for weight value selection in DNN.

• To prove the effectiveness of the proposed algorithms.

摘要

•Several operations are handled for bi-traits-centered offender identification.•Image quality is highly increased by the proposed method of offender identification.•The system solves the computation issues of tree structure part model.•A new way is used for weight value selection in DNN.•To prove the effectiveness of the proposed algorithms.

论文关键词：Forensic science,Forensic evidence,Criminal investigation,Fingerprint identification,Facial image identification,Deep neural network

论文评审过程：Received 25 October 2021, Revised 24 February 2022, Accepted 23 April 2022, Available online 27 April 2022, Version of Record 4 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117313