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Analysis of institutional authors

Bejani MAuthor

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July 25, 2020
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Audio-visual emotion recognition using FCBF feature selection method and particle swarm optimization for fuzzy ARTMAP neural networks

Publicated to:Multimedia Tools And Applications. 76 (2): 2331-2352 - 2017-01-01 76(2), DOI: 10.1007/s11042-015-3180-6

Authors: Gharavian D; Bejani M; Sheikhan M

Affiliations

Islamic Azad University, South Tehran Branch - Author
Shahid Beheshti University - Author

Abstract

© 2016, Springer Science+Business Media New York. Humans use many modalities such as face, speech and body gesture to express their feeling. So, to make emotional computers and make the human-computer interaction (HCI) more naturally and friendly, computers should be able to understand human feelings using speech and visual information. In this paper, we recognize the emotions from audio and visual information using fuzzy ARTMAP neural network (FAMNN). Audio and visual systems fuse at decision and feature levels. Finally, the particle swarm optimization (PSO) is employed to determine the optimum values of the choice parameter (α), the vigilance parameters (ρ), and the learning rate (β) of the FAMNN. Experimental results showed that the feature-level and decision-level fusions improve the outcome of unimodal systems. Also PSO improved the recognition rate. By using the PSO-optimized FAMNN at feature level fusion, the recognition rate was improved by about 57 % with respect to the audio system and by about 4.5 % with respect to the visual system. The final emotion recognition rate on the SAVEE database was reached to 98.25 % using audio and visual features by using optimized FAMNN.

Keywords

Audio-visual emotion recognitionFuzzy artmap neural networkParticle swarm optimization

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Multimedia Tools And Applications due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2017, it was in position 42/104, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Computer Science, Software Engineering. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría Computer Networks and Communications.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 1.11. This indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: ESI Nov 14, 2024)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Weighted Average of Normalized Impact by the Scopus agency: 1.71 (source consulted: FECYT Feb 2024)
  • Field Citation Ratio (FCR) from Dimensions: 8.01 (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-28, the following number of citations:

  • WoS: 25
  • Scopus: 42

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-28:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 51 (PlumX).

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Iran.