부산대학교 도서관

The necessity towards technology that can distinguish, discover and recognize culprits is skyrocketing nowadays. For crime investigations and forensics experts in Machine Vision, analyzing and interpreting how individuals recognize face portraits created by forensics illustrators is critical. In government validation and surveillance, connecting the drawing to the photographs is critical since it has been used to monitor culprits or perpetrators. Suspects have been known to wear customized masks to conceal common facial traits such as the nose, eyes, lips, and color. However, the bottom - level aspects of facial biometrics cannot be eliminated. For this, it was focused on a few human face geometry elements that may be utilized to determine correspondent rates between the prototype Photographic databases and the analytical artworks. The construction of a system for forensic facial drawing authentication using deep learning algorithms is described in this work.
Notice of Violation of IEEE Publication Principles “Deep Learning based Forensic Face Sketch Recognition” by R. Naga Sravana Jyothi; G. Bhargavi; M. Gowthami; B. Dhana Lakshmi; V. Tejaswi in the Proceedings of the International Conference on Electronics and Renewable Systems (ICEARS), March 2022 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. This paper copied content from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. “Forensic Face Photo-Sketch Recognition Using a Deep Learning-Based Architecture” by Christian Galea and Reuben A. Farrugia in the IEEE Signal Processing Letters, Vol 24, No 11, November 2017