Emerging Biometrics: Deep Inference and Other Computational Intelligence
This work targets researchers developing next-generation intelligent biometric systems, but it is incremental as it reviews existing trends without presenting new methods or results.
The paper identifies emerging computational intelligence trends, such as deep learning and deep inference, for designing complex biometric-enabled systems, highlighting technology gaps that need to be addressed in future generations.
This paper aims at identifying emerging computational intelligence trends for the design and modeling of complex biometric-enabled infrastructure and systems. Biometric-enabled systems are evolving towards deep learning and deep inference using the principles of adaptive computing, - the front tides of the modern computational intelligence domain. Therefore, we focus on intelligent inference engines widely deployed in biometrics. Computational intelligence applications that cover a wide spectrum of biometric tasks using physiological and behavioral traits are chosen for illustration. We highlight the technology gaps that must be addressed in future generations of biometric systems. The reported approaches and results primarily address the researchers who work towards developing the next generation of intelligent biometric-enabled systems.