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Extreme Learning Machine (ELM) has been introduced as a new algorithm for training single hidden layer feed-forward neural networks (SLFNs) instead of the classical gradient-based algorithms. Based on the consistency property of data, which enforce similar samples to share similar properties, ELM is a biologically inspired learning algorithm with SLFNs that learns much faster with good generalization...
The permutation coding neural classifier (PCNC) and its application to face recognition are described. Face recognition is a very important task in security applications such as those in airports and other institutions and for authentication via photo tagging in social networks. It is possible to improve face recognition with the PCNC using special types of distortion applied to the original images...
This paper investigates three approaches to the problem of identity recognition in real-world unconstrained environments. We describe a new and challenging face recognition dataset captured in a laboratory environment with no strong constraints on lighting, motion, or subject pose, orientation, distance, or facial expression. We then evaluate three approaches to identity recognition on this new dataset...
Automatic facial expression recognition plays an important role in agent-based interface development and datadriven animation. This paper presents an intelligent facial action and emotion recognition system for a humanoid robot. Motivated by the Facial Action Coding System, this research focuses on the recognition of seven basic emotions and 18 Action Units (AU). Since effective facial representations...
In recent years, human identification based on face recognition has attracted the attention of the scientific community and the general public due to its wide range of applications. A face recognition system involves three important phases: face detection, feature extraction and classification (identification and/or verification). The robustness of face recognition could be improved by treating the...
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