Advances in Pattern Analysis for Identity Recognition and Verification

Dear Colleagues,

Currently we are witnesses of the fourth industrial revolution also known as Industry 4.0 in Europe, Society 5.0 in Japan and Industrial Internet of Things (IIT) in USA. The main characteristics of this new living model is the massive interaction of humans with machines (smartphones, computers, social robots, etc.) the generation, storing and processing of big data using A.I. algorithms and Internet of Things (IoT).

In this context, there is a continuous increasing need to identify humans and entities in general, by analyzing their patterns. For example, in the coming years humans will interact with the ATM machines without using debit cards but with their biometrics.

Although a significant progress is reported recently, in the field of biometrics by incorporating deep learning models, the task of identifying someone under varying conditions is still open. For example, human identification in the wild or using only few samples of data are cases that worth more attention and research towards better analysis of the patterns describing the identities.

This Special issue aims to summarize the recent advances in extracting and analyzing patterns that are able to identify the owner of them. Topics may include, but are not limited to:

• Face recognition/verification
• Iris recognition/verification
• Fingerprint recognition/verification
• Ear recognition/verification
• Vein recognition/verification
• Gait recognition/verification
• EEG recognition/verification
• Behavioral biometrics
• Multimodal and adaptive biometric systems
• Adversarial machine learning for biometric systems
• Feature extraction
• Storing and processing big biometric data
• New biometric systems architectures
• New benchmark datasets
• New applications

Prof. Dr. George A. Papakostas
Guest Editor

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