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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A snapshot research and implementation of multimodal information fusion for data-driven emotion recognition
Yingying Jiang, Wei Li, M. Shamim Hossain, et al.
Information Fusion (2019) Vol. 53, pp. 209-221
Closed Access | Times Cited: 165

Showing 1-25 of 165 citing articles:

A Metaverse: Taxonomy, Components, Applications, and Open Challenges
Sangmin Park, Young‐Gab Kim
IEEE Access (2022) Vol. 10, pp. 4209-4251
Open Access | Times Cited: 1307
A systematic review on affective computing: emotion models, databases, and recent advances
Yan Wang, Wei Song, Wei Tao, et al.
Information Fusion (2022) Vol. 83-84, pp. 19-52
Open Access | Times Cited: 290
A survey of emotion recognition methods with emphasis on E-Learning environments
Maryam Imani, Gholam Ali Montazer
Journal of Network and Computer Applications (2019) Vol. 147, pp. 102423-102423
Closed Access | Times Cited: 144
Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects
Shiqing Zhang, Yijiao Yang, Chen Chen, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121692-121692
Closed Access | Times Cited: 75
Comprehensive systematic review of information fusion methods in smart cities and urban environments
Mohammed A. Fadhel, Ali M. Duhaim, Ahmed Saihood, et al.
Information Fusion (2024) Vol. 107, pp. 102317-102317
Open Access | Times Cited: 65
Emotion recognition from unimodal to multimodal analysis: A review
Kaouther Ezzameli, Hela Mahersia
Information Fusion (2023) Vol. 99, pp. 101847-101847
Closed Access | Times Cited: 64
Multi-modality approaches for medical support systems: A systematic review of the last decade
Massimo Salvi, Hui Wen Loh, Silvia Seoni, et al.
Information Fusion (2023) Vol. 103, pp. 102134-102134
Open Access | Times Cited: 54
Multimodal Emotion Recognition with Deep Learning: Advancements, challenges, and future directions
Geetha Vijayaraghavan, T. Mala, Das P, et al.
Information Fusion (2023) Vol. 105, pp. 102218-102218
Closed Access | Times Cited: 53
Multi-source information fusion: Progress and future
Xinde Li, Fir Dunkin, Jean Dezert
Chinese Journal of Aeronautics (2023) Vol. 37, Iss. 7, pp. 24-58
Open Access | Times Cited: 43
From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications
Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, et al.
Brain Sciences (2025) Vol. 15, Iss. 3, pp. 220-220
Open Access | Times Cited: 1
A survey of speech emotion recognition in natural environment
Md Shah Fahad, Ashish Ranjan, Jainath Yadav, et al.
Digital Signal Processing (2020) Vol. 110, pp. 102951-102951
Closed Access | Times Cited: 120
A Human–Computer Interaction framework for emotion recognition through time-series thermal video sequences
Satyajit Nayak, B S Nagesh, Aurobinda Routray, et al.
Computers & Electrical Engineering (2021) Vol. 93, pp. 107280-107280
Closed Access | Times Cited: 62
Information fusion for edge intelligence: A survey
Yin Zhang⋆, Chi Jiang, Binglei Yue, et al.
Information Fusion (2021) Vol. 81, pp. 171-186
Closed Access | Times Cited: 58
Multi-modal emotion recognition using EEG and speech signals
Qian Wang, Mou Wang, Yan Yang, et al.
Computers in Biology and Medicine (2022) Vol. 149, pp. 105907-105907
Closed Access | Times Cited: 56
An octonion-based nonlinear echo state network for speech emotion recognition in Metaverse
Fatemeh Daneshfar, Mohammad Jamshidi
Neural Networks (2023) Vol. 163, pp. 108-121
Closed Access | Times Cited: 34
A review of multimodal emotion recognition from datasets, preprocessing, features, and fusion methods
Bei Pan, Kaoru Hirota, Zhiyang Jia, et al.
Neurocomputing (2023) Vol. 561, pp. 126866-126866
Closed Access | Times Cited: 33
Big Data and AI-Driven Product Design: A Survey
Huafeng Quan, Shaobo Li, Changchang Zeng, et al.
Applied Sciences (2023) Vol. 13, Iss. 16, pp. 9433-9433
Open Access | Times Cited: 24
Emotion recognition based on multiple physiological signals
Qi Li, Yunqing Liu, Fei Yan, et al.
Biomedical Signal Processing and Control (2023) Vol. 85, pp. 104989-104989
Closed Access | Times Cited: 23
Enhancing emotion recognition using multimodal fusion of physiological, environmental, personal data
Hakpyeong Kim, Taehoon Hong
Expert Systems with Applications (2024) Vol. 249, pp. 123723-123723
Closed Access | Times Cited: 11
Enhanced multimodal emotion recognition in healthcare analytics: A deep learning based model-level fusion approach
Md. Milon Islam, Sheikh Nooruddin, Fakhri Karray, et al.
Biomedical Signal Processing and Control (2024) Vol. 94, pp. 106241-106241
Closed Access | Times Cited: 9
Exploring contactless techniques in multimodal emotion recognition: insights into diverse applications, challenges, solutions, and prospects
Umair Ali Khan, Qianru Xu, Yang Liu, et al.
Multimedia Systems (2024) Vol. 30, Iss. 3
Open Access | Times Cited: 9
Hybrid multimodal fusion with deep learning for rolling bearing fault diagnosis
Changchang Che, Huawei Wang, Xiaomei Ni, et al.
Measurement (2020) Vol. 173, pp. 108655-108655
Closed Access | Times Cited: 62
HetEmotionNet
Ziyu Jia, Youfang Lin, Jing Wang, et al.
Proceedings of the 30th ACM International Conference on Multimedia (2021), pp. 1047-1056
Closed Access | Times Cited: 48
Identifying content unaware features influencing popularity of videos on YouTube: A study based on seven regions
Zahid Halim, Sajjad Hussain, Raja Hashim Ali
Expert Systems with Applications (2022) Vol. 206, pp. 117836-117836
Closed Access | Times Cited: 34
Deep Learning Approach for Detecting Work-Related Stress Using Multimodal Signals
Wonju Seo, Nam‐Ho Kim, Cheolsoo Park, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 12, pp. 11892-11902
Closed Access | Times Cited: 34
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