Advanced Technologies for Emotion Recognition
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 May 2024 | Viewed by 17341
Special Issue Editors
Interests: computer science; statistical machine learning; artificial intelligence
Interests: social network analysis; social media data mining; network events detection and influence analysis and prediction; network multimodal data deep fusion; text data information extraction; multimodal deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: human behaviour analysis; pattern recognition; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the development of computing technology and human-computer interaction technology, emotion recognition technology has gradually become an important research topic in human-like artificial intelligence (AI). It is widely used in healthcare, education, public service, and social network analysis. The content of emotion recognition research includes facial expressions, speech, heart rate, behavior, text and physiological signal recognition, etc., through which the user’s emotional state can be judged.
We invite original research papers and review articles on emotion recognition innovations, including but not limited to any of the following emotion recognition-related topics:
- Systems and devices for capturing physiological signals;
- Data preprocessing;
- Non-invasive sensor technology;
- Machine learning techniques for emotion recognition;
- Deep learning for emotion recognition;
- Facial expression recognition;
- Audio analysis for emotion recognition;
- Brain signals analysis for emotion recognition;
- Behavior analysis for emotion recognition;
- Emotional model;
- Explainable models for emotion recognition.
Dr. Xavier Solé
Dr. Xiaoming Zhang
Prof. Dr. Sergio Escalera
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Emotion Recognition Using Audio-Visual Features
Author:
Highlights: This paper tries to find a common ground for people across various cultures speaking the same language. In a real-world scenario, speech/images/videos might not be perfect in the way the datasets are collected.
Title: Systematic Review: Emotion Recognition based on Electrophysiological Patterns for Emotion Regulation Detection
Author: Ibarra-Zarate
Highlights: Electrophysiological signals; Emotional Intelligence; Emotion Recognition; Emotion Regulation; Methodology