Deep Learning for Diagonal Earlobe Crease Detection

Bibliographic Details
Title: Deep Learning for Diagonal Earlobe Crease Detection
Authors: Almonacid-Uribe, Sara L., Santana, Oliverio J., Hernández-Sosa, Daniel, Freire-Obregón, David
Publication Year: 2022
Collection: Computer Science
Subject Terms: Computer Science - Computer Vision and Pattern Recognition
More Details: An article published on Medical News Today in June 2022 presented a fundamental question in its title: Can an earlobe crease predict heart attacks? The author explained that end arteries supply the heart and ears. In other words, if they lose blood supply, no other arteries can take over, resulting in tissue damage. Consequently, some earlobes have a diagonal crease, line, or deep fold that resembles a wrinkle. In this paper, we take a step toward detecting this specific marker, commonly known as DELC or Frank's Sign. For this reason, we have made the first DELC dataset available to the public. In addition, we have investigated the performance of numerous cutting-edge backbones on annotated photos. Experimentally, we demonstrate that it is possible to solve this challenge by combining pre-trained encoders with a customized classifier to achieve 97.7% accuracy. Moreover, we have analyzed the backbone trade-off between performance and size, estimating MobileNet as the most promising encoder.
Comment: Accepted at 12th International Conference on Pattern Recognition Applications (ICPRAM 2023)
Document Type: Working Paper
DOI: 10.5220/0011644400003411
Access URL: http://arxiv.org/abs/2210.11582
Accession Number: edsarx.2210.11582
Database: arXiv
More Details
DOI:10.5220/0011644400003411