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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:

An approach for automatically measuring facial activity in depressed subjects
Gordon McIntyre, Roland Göcke, Matthew P. Hyett, et al.
(2009)
Closed Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

A review of depression and suicide risk assessment using speech analysis
Nicholas Cummins, Stefan Scherer, Jarek Krajewski, et al.
Speech Communication (2015) Vol. 71, pp. 10-49
Closed Access | Times Cited: 767
Automatic Assessment of Depression Based on Visual Cues: A Systematic Review
Anastasia Pampouchidou, Panagiotis G. Simos, Kostas Marias, et al.
IEEE Transactions on Affective Computing (2017) Vol. 10, Iss. 4, pp. 445-470
Open Access | Times Cited: 183
Deep learning for depression recognition with audiovisual cues: A review
Lang He, Mingyue Niu, Prayag Tiwari, et al.
Information Fusion (2021) Vol. 80, pp. 56-86
Open Access | Times Cited: 129
Automatic Diagnosis of Depression Based on Facial Expression Information and Deep Convolutional Neural Network
Mi Li, Yuqi Wang, Chuang Yang, et al.
IEEE Transactions on Computational Social Systems (2024) Vol. 11, Iss. 5, pp. 5728-5739
Closed Access | Times Cited: 22
An investigation of depressed speech detection: features and normalization
Nicholas Cummins, Julien Epps, Michael Breakspear, et al.
Interspeech 2022 (2011)
Closed Access | Times Cited: 174
Multimodal assistive technologies for depression diagnosis and monitoring
Jyoti Joshi, Roland Goecke, Sharifa Alghowinem, et al.
Journal on Multimodal User Interfaces (2013) Vol. 7, Iss. 3, pp. 217-228
Open Access | Times Cited: 166
Predicting Depression, Anxiety, and Stress Levels from Videos Using the Facial Action Coding System
Mihai Gavrilescu, Nicolae Vizireanu
Sensors (2019) Vol. 19, Iss. 17, pp. 3693-3693
Open Access | Times Cited: 118
Diagnosis of depression by behavioural signals
Nicholas Cummins, Jyoti Joshi, Abhinav Dhall, et al.
(2013), pp. 11-20
Open Access | Times Cited: 117
New Measures of Mental State and Behavior Based on Data Collected From Sensors, Smartphones, and the Internet
Tasha Glenn, Scott Monteith
Current Psychiatry Reports (2014) Vol. 16, Iss. 12
Closed Access | Times Cited: 113
Can body expressions contribute to automatic depression analysis?
Jyoti Joshi, Roland Goecke, Gordon Parker, et al.
(2013), pp. 1-7
Closed Access | Times Cited: 105
Detecting depression: A comparison between spontaneous and read speech
Sharifa Alghowinem, Roland Goecke, Michael Wagner, et al.
IEEE International Conference on Acoustics Speech and Signal Processing (2013), pp. 7547-7551
Closed Access | Times Cited: 105
Vision-based patient monitoring: a comprehensive review of algorithms and technologies
Supriya Sathyanarayana, Ravi Kumar Satzoda, Suchitra Sathyanarayana, et al.
Journal of Ambient Intelligence and Humanized Computing (2015) Vol. 9, Iss. 2, pp. 225-251
Closed Access | Times Cited: 104
Audio based depression detection using Convolutional Autoencoder
Sara Sardari, Bahareh Nakisa, Mohammad Naim Rastgoo, et al.
Expert Systems with Applications (2021) Vol. 189, pp. 116076-116076
Closed Access | Times Cited: 69
Sentiment analysis and affective computing for depression monitoring
Chiara Zucco, Barbara Calabrese, Mario Cannataro
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2017), pp. 1988-1995
Closed Access | Times Cited: 78
From Joyous to Clinically Depressed: Mood Detection Using Spontaneous Speech
Sharifa Alghowinem, Roland Goecke, Michael Wagner, et al.
(2012), pp. 141-146
Closed Access | Times Cited: 75
Deep Neural Networks for Depression Recognition Based on 2D and 3D Facial Expressions Under Emotional Stimulus Tasks
Weitong Guo, Hongwu Yang, Zhenyu Liu, et al.
Frontiers in Neuroscience (2021) Vol. 15
Open Access | Times Cited: 49
Design and Implementation of Attention Depression Detection Model Based on Multimodal Analysis
Junhee Park, Nammee Moon
Sustainability (2022) Vol. 14, Iss. 6, pp. 3569-3569
Open Access | Times Cited: 29
Let’s Face It: Influence of Facial Expressions on Social Presence in Collaborative Virtual Reality
Simon Kimmel, Frederike Jung, Andrii Matviienko, et al.
(2023), pp. 1-16
Closed Access | Times Cited: 16
Automatic Nonverbal Behavior Indicators of Depression and PTSD: Exploring Gender Differences
Giota Stratou, Stefan Scherer, Jonathan Gratch, et al.
(2013), pp. 147-152
Closed Access | Times Cited: 64
Depression Estimation Using Audiovisual Features and Fisher Vector Encoding
Varun Jain, James L. Crowley, Anind K. Dey, et al.
(2014), pp. 87-91
Open Access | Times Cited: 64
Automated screening for distress: A perspective for the future
Rajib Rana, Siddique Latif, Raj Gururajan, et al.
European Journal of Cancer Care (2019) Vol. 28, Iss. 4
Open Access | Times Cited: 47
Automatic nonverbal behavior indicators of depression and PTSD: the effect of gender
Giota Stratou, Stefan Scherer, Jonathan Gratch, et al.
Journal on Multimodal User Interfaces (2014) Vol. 9, Iss. 1, pp. 17-29
Closed Access | Times Cited: 51
Modeling spectral variability for the classification of depressed speech
Nicholas Cummins, Julien Epps, Vidhyasaharan Sethu, et al.
Interspeech 2022 (2013), pp. 857-861
Closed Access | Times Cited: 50
Relative Body Parts Movement for Automatic Depression Analysis
Jyoti Joshi, Abhinav Dhall, Roland Goecke, et al.
(2013), pp. 492-497
Closed Access | Times Cited: 47
Facial expression video analysis for depression detection in Chinese patients
Qingxiang Wang, Huanxin Yang, Yanhong Yu
Journal of Visual Communication and Image Representation (2018) Vol. 57, pp. 228-233
Closed Access | Times Cited: 45
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