About IEEE T-BIOM
The IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM) publishes original articles on all aspects of biometrics (i.e. recognizing people through their physiological or behavioral traits such as face, fingerprint, iris, and signature), including theory, applications, systems, and surveys. Biometrics are personal identity characteristics where people are recognized by who they are rather than by what they own; behavior is the typical movement of a person that is unique and identifiable; identity science underlies the application of biometrics. Papers focusing on ramifications of these areas will also be welcomed, such as security of such systems, standards for their deployment, and new architectures and systems are also welcomed. Broad topics of interest include but are not limited to:
- Biometric modalities and their fusion
- Novel pattern classification and machine learning, including deep learning, algorithms for biometrics and identity science
- Behavior analysis related to biometrics and identity science
- Security of biometrics and identity systems
- Applications including forensics, healthcare, and law enforcement
Find archived issues of the IEEE Biometrics Council Compendium →
T-BIOM News
Prof. Nalini K. Ratha Joins Us As EIC TBIOM
IEEE Biometrics Council is happy to introduce the new Editor-in-Chief of the IEEE Transactions of Biometrics and Identity Science. The new Editor-in-Chief is Professor Nalini Ratha and his term will be from July 2021 to June 2024. Prof. Ratha is [...]
Call for Applications for the ‘Editor-in-Chief’ of IEEE Transactions on Biometrics, Behavior and Identity Science (TBIOM)
The IEEE Biometrics Council invites applications for the Editor-in-Chief of the IEEE Trans. on Biometrics, Behavior and Identity Science. The term is for three years. The applicants must have strong, relevant experience in roles such as author, reviewer, and area/associate [...]
Call for papers IEEE Transactions on Biometrics, Behavior, and Identity Science Special Issue on Face Presentation Attack Detection
Face anti-spoofing recognition is a hot and challenging research topic that has received much attention from the computer vision and pattern recognition communities in the past. Owing to the development of deep learning and big data, recent advances of the [...]
