Тип публикации: статья из журнала
Год издания: 2019
Ключевые слова: evolutionary algorithm, Multimodal pain intensity recognition, neural network
Аннотация: In this paper we present a study on multi-modal pain intensity recognition based on video and bio-physiological sensor data. The newly recorded SenseEmotion dataset consisting of 40 individuals, each subjected to three gradually increasing levels of painful heat stimuli, has been used for the evaluation of the proposed algorithms. We propose and evaluated evolutionary algorithms for the design and adaptation of the structure of deep artificial neural network architectures. Feedforward Neural Network and Recurrent Neural Network have been considered for the optimisation by using a Self-Configuring Genetic Algorithm (SelfCGA) and Self-Configuring Genetic Programming (SelfCGP).
Издание
Журнал: Lecture Notes in Computer Science (см. в книгах)
Выпуск журнала: Т.11377 LNAI
Номера страниц: 84-100
ISSN журнала: 03029743
Издатель: Springer-Verlag GmbH
Персоны
- Mamontov D. (Reshetnev Siberian State University of Science and Technology)
- Polonskaia I. (Reshetnev Siberian State University of Science and Technology)
- Skorokhod A. (Reshetnev Siberian State University of Science and Technology)
- Semenkin E. (Reshetnev Siberian State University of Science and Technology)
- Kessler V. (Institute of Neural Information Processing,Ulm University)
- Schwenker F. (Institute of Neural Information Processing,Ulm University)
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