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SI-ML4Biometrics 2020 : Special Issue on Advanced Machine Learning Algorithms for Biometrics and Its Applications | |||||||||||
Link: https://www.mdpi.com/journal/applsci/special_issues/Machine_Learning_Biometrics | |||||||||||
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Call For Papers | |||||||||||
Special Issue Information
Biometrics has become a burgeoning research area due to the industrial and government needs for recognition and security concerns. It has also become a center of focus for many applications, such as identity authentication and identification in civil and forensic fields. Recently, advanced machine learning has received a great deal of attention in solving difficult and complex problems related to biometric recognition and security, where conventional machine learning techniques have shown their limitations. This Special Issue aims to solicit original research papers, as well as review articles focusing on biometrics and its applications based on advanced machine learning algorithms. We are inviting original research works covering novel theories, innovative methods, and meaningful applications that can potentially lead to significant advances in the biometrics domain. In addition, the authors of the papers which will be presented at the 4th International Workshop on “Recent Advances in Biometrics and its Applications” that we are organizing in conjunction with the 43rd International Conference on Telecommunications and Signal Processing (TSP) will be invited to submit an extended version of their papers to this Special Issue after the conference. Submitted papers should be extended to the size of regular research or review articles, with at least a 50% extension of new results. There are no page limitations for this journal. Topics of interest include but are not limited to the following: - Biometrics-based authentication and identification; - Physiological and behavioral biometrics (e.g., finger, palm, face, eye, ear, iris, retina, vein, gait, handwriting, voice); - Biometric feature extraction and matching; - Signal, image, and video processing in biometrics; - Advanced pattern recognition in biometrics; - Machine learning and deep learning in biometrics; - Artificial intelligence in biometrics; - Fusion techniques in biometrics; - Soft biometrics; - Multimodal biometrics; - Security and privacy in biometrics; - Big data challenges in biometrics; - Embedded biometric systems; - Emerging biometrics; - Related applications. Guest Editors Assoc. Prof. Dr. Larbi Boubchir Prof. Dr. Elhadj Benkhelifa Prof. Dr. Boubaker Daachi |
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