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Measuring human emotions with modular neural networks and computer vision based applications
Authors: Albu Veaceslav, Cojocaru Svetlana
Keywords: Neural networks, emotion recognition, RBFN modular neural networks, Kinect.
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Keywords: Neural networks, emotion recognition, RBFN modular neural networks, Kinect.
Abstract
This paper describes a neural network architecture for emotion recognition for human-computer interfaces and applied systems. In the current research, we propose a combination of the most recent biometric techniques with the neural networks (NN) approach for real-time emotion and behavioral analysis. The system will be tested in real-time applications of customers' behavior for distributed on-land systems, such as kiosks and ATMs.Institute of Mathematics and Computer Science
Academy of Sciences of Moldova
5 Academiei str., Chisinau, MD-2028, Moldova
E-mail: ,
Academy of Sciences of Moldova
5 Academiei str., Chisinau, MD-2028, Moldova
E-mail: ,
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
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Contents
- Bounds on Global Total Domination in Graphs
- Construction of a transitive orientation using B-stable subgraphs
- Maximum Inaccuracies of Second Order
- Measuring human emotions with modular neural networks and computer vision based applications
- Provably sender-deniable encryption scheme
- Modeling of meaning acquisition based on NL phrases using state transitions
- Identity, Ontology, and Frege's Problem
- Towards an Ontology of Individuals: Comments on "Identity, Ontology and Frege's Problem" of William Greenberg