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Spoken emotion recognition using hierarchical classifiers
(Elsevier, 2011-07)
The recognition of the emotional state of speakers is a multi-disciplinary research area that has received great interest over the last years. One of the most important goals is to improve the voice-based human-machine ...
Novel approaches for exclusive and continuous fingerprint classification
(Scopus, 2009)
This paper proposes novel exclusive and continuous approaches to guide the search and the retrieval in fingerprint image databases. Both approaches are useful to perform a coarse level classification of fingerprint images ...
Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition
(Institute of Electrical and Electronics Engineers Inc., 2020-09-01)
In peruvian sign language (PSL), recognition of static gestures has been proposed earlier. However, to state a conversation using sign language, it is also necessary to employ dynamic gestures. We propose a method to extract ...
A multimodal emotion recognition method based on facial expressions and electroencephalography
(Elsevier, 2021-09)
Human-robot interaction (HRI) systems play a critical role in society. However, most HRI systems nowadays still face the challenge of disharmony, resulting in an inefficient communication between the human and the robot. ...
Denoising and recognition using hidden Markov models with observation distributions modeled by hidden Markov trees
(Elsevier, 2010-04)
Hidden Markov models have been found very useful for a wide range of applications in machine learning and pattern recognition. The wavelet transform has emerged as a new tool for signal and image analysis. Learning models ...
Multi-view stacking for activity recognition with sound and accelerometer data
(Elsevier, 2018-03-10)
Many Ambient Intelligence (AmI) systems rely on automatic human activity recognition for getting crucial context information, so that they can provide personalized services based on the current users’ state. Activity ...
Semi-supervised 3D object recognition through CNN labeling
(04/01/2018)
Despite the outstanding results of Convolutional Neural Networks (CNNs) in object recognition and classification, there are still some open problems to address when applying these solutions to real-world problems. Specifically, ...