Matthias Rätsch

1.1k total citations
34 papers, 579 citations indexed

About

Matthias Rätsch is a scholar working on Computer Vision and Pattern Recognition, Social Psychology and Applied Psychology. According to data from OpenAlex, Matthias Rätsch has authored 34 papers receiving a total of 579 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 10 papers in Social Psychology and 6 papers in Applied Psychology. Recurrent topics in Matthias Rätsch's work include Face recognition and analysis (7 papers), Face and Expression Recognition (7 papers) and Mental Health via Writing (5 papers). Matthias Rätsch is often cited by papers focused on Face recognition and analysis (7 papers), Face and Expression Recognition (7 papers) and Mental Health via Writing (5 papers). Matthias Rätsch collaborates with scholars based in Germany, China and United Kingdom. Matthias Rätsch's co-authors include Junfeng Jing, Huanhuan Zhang, Zhen Wang, Lei Chen, Xiaohua Li, Zhaohua Liu, Patrik Huber, Hua‐Liang Wei, Biliang Lu and Josef Kittler and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Image Processing.

In The Last Decade

Matthias Rätsch

29 papers receiving 553 citations

Peers

Matthias Rätsch

CVPR

IME

CSE

Gyogwon Koo South Korea

Bing Wei China

Modris Greitāns Latvia

Ziji Ma China

Joo-Haeng Lee South Korea

Ruiyu Liang China

Xiaogang Jin China

Ke Jiang China

Chen-Chiung Hsieh Taiwan

Qingsheng Xie China

Gyogwon Koo South Korea

Matthias Rätsch

181 ×0.7

CVPR

189 ×1.4

IME

134 ×1.2

CSE

56 ×0.6

118 ×1.4

Citations per year, relative to Matthias Rätsch Matthias Rätsch (= 1×) peers Gyogwon Koo

Countries citing papers authored by Matthias Rätsch

Since Specialization

Citations

This map shows the geographic impact of Matthias Rätsch's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matthias Rätsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Rätsch more than expected).

Fields of papers citing papers by Matthias Rätsch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthias Rätsch. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthias Rätsch. The network helps show where Matthias Rätsch may publish in the future.

Co-authorship network of co-authors of Matthias Rätsch

This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Rätsch. A scholar is included among the top collaborators of Matthias Rätsch based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthias Rätsch. Matthias Rätsch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Yuan, Shenghai, et al.. (2025). Natural Multimodal Fusion-Based Human–Robot Interaction: Application With Voice and Deictic Posture via Large Language Model. IEEE Robotics & Automation Magazine. 2–11. 1 indexed citations

Guo, Yuchen, et al.. (2025). Enhancing Individual Self-Efficacy Through a Self-Growing Memory Artificial Intelligence Agent Integrated with a Diary Application. Journal of Advanced Computational Intelligence and Intelligent Informatics. 29(1). 41–52. 1 indexed citations

Kubota, Naoyuki, et al.. (2025). Hearing emotions: fine-tuning speech emotion recognition models. Reutlingen University Academic Bibliography (Reutlingen University). 18–18.

Yuan, Shenghai, et al.. (2025). NVP-HRI: Zero shot natural voice and posture-based human–robot interaction via large language model. Expert Systems with Applications. 268. 126360–126360. 2 indexed citations

Kubota, Naoyuki, et al.. (2024). Zero-Shot Strike: Testing the generalisation capabilities of out-of-the-box LLM models for depression detection. Computer Speech & Language. 88. 101663–101663. 15 indexed citations

Fox, J. H., et al.. (2024). GPT-4 shows potential for identifying social anxiety from clinical interview data. Scientific Reports. 14(1). 30498–30498. 2 indexed citations

Rätsch, Matthias, et al.. (2024). Unsupervised question-retrieval approach based on topic keywords filtering and multi-task learning. Computer Speech & Language. 87. 101644–101644. 2 indexed citations

Rätsch, Matthias, et al.. (2024). Self-Categorization Theory with 3D Emotional Model for Chatbot Emotional Support Systems. Reutlingen University Academic Bibliography (Reutlingen University). 46. 267–272. 1 indexed citations

Zhang, Yihong, et al.. (2024). Enhancing early depression detection with AI: a comparative use of NLP models. SHILAP Revista de lepidopterología. 17(1). 135–143. 3 indexed citations

10.

Rätsch, Matthias, et al.. (2024). Panic consumption under public health emergencies: The mediating role of risk perception. Journal of Public Health. 33(10). 2267–2277. 2 indexed citations

11.

Shiban, Youssef, et al.. (2024). AI-Supported Diagnostic of Depression Using Clinical Interviews: A Pilot Study. Reutlingen University Academic Bibliography (Reutlingen University). 500–507. 3 indexed citations

12.

Kyosev, Yordan, et al.. (2024). AI-assisted Pattern Generator for Garment Design. SHILAP Revista de lepidopterología. 5(2). 195–206. 1 indexed citations

13.

Ren, Jie, et al.. (2023). Pre-training neural machine translation with alignment information via optimal transport. Multimedia Tools and Applications. 83(16). 48377–48397.

14.

Shiban, Youssef, et al.. (2023). Advancing Mental Health Diagnostics: GPT-Based Method for Depression Detection. Reutlingen University Academic Bibliography (Reutlingen University). 1290–1296. 14 indexed citations

15.

Jing, Junfeng, Zhen Wang, Matthias Rätsch, & Huanhuan Zhang. (2020). Mobile-Unet: An efficient convolutional neural network for fabric defect detection. Textile Research Journal. 92(1-2). 30–42. 206 indexed citations

16.

Rätsch, Matthias, et al.. (2018). An interactive clothing design and personalized virtual display system. Multimedia Tools and Applications. 77(20). 27163–27179. 21 indexed citations

17.

Huber, Patrik, et al.. (2016). A Multiresolution 3D Morphable Face Model and Fitting Framework. View. 79–86. 128 indexed citations

18.

Rätsch, Matthias, et al.. (2010). 3D Cascaded Condensation Tracking for Multiple Objects. 1 indexed citations

19.

Rätsch, Matthias, et al.. (2009). Coarse-to-fine particle filters for multi-object human computer interaction. 1. 440–445. 4 indexed citations

20.

Rätsch, Matthias, Gerd Teschke, Sami Romdhani, & Thomas Vetter. (2008). Wavelet Frame Accelerated Reduced Support Vector Machines. IEEE Transactions on Image Processing. 17(12). 2456–2464. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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