Chung-Chian Hsu

1.2k total citations
52 papers, 743 citations indexed

About

Chung-Chian Hsu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Chung-Chian Hsu has authored 52 papers receiving a total of 743 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 10 papers in Signal Processing. Recurrent topics in Chung-Chian Hsu's work include Neural Networks and Applications (17 papers), Advanced Clustering Algorithms Research (14 papers) and Face and Expression Recognition (10 papers). Chung-Chian Hsu is often cited by papers focused on Neural Networks and Applications (17 papers), Advanced Clustering Algorithms Research (14 papers) and Face and Expression Recognition (10 papers). Chung-Chian Hsu collaborates with scholars based in Taiwan, United States and Pakistan. Chung-Chian Hsu's co-authors include Shahab S. Band, Rasoul Ameri, Yu‐Cheng Chen, Chin-Long Chen, Yu-Wei Su, Mehdi Sookhak, Anthony T. Chronopoulos, Abdollah Dehzangi, Huey‐Wen Liang and Wei‐Hao Huang and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Chung-Chian Hsu

45 papers receiving 693 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chung-Chian Hsu Taiwan 16 411 140 115 105 53 52 743
J. Anuradha India 11 352 0.9× 126 0.9× 176 1.5× 91 0.9× 36 0.7× 31 942
Qingchen Zhang China 3 327 0.8× 152 1.1× 91 0.8× 64 0.6× 28 0.5× 5 816
Honghui Xu United States 11 343 0.8× 168 1.2× 80 0.7× 89 0.8× 48 0.9× 22 808
Matthias Feurer Germany 6 651 1.6× 128 0.9× 92 0.8× 57 0.5× 123 2.3× 9 1.0k
Belal Al‐Khateeb Iraq 15 396 1.0× 119 0.8× 38 0.3× 63 0.6× 37 0.7× 66 743
André Luis Debiaso Rossi Brazil 11 361 0.9× 100 0.7× 51 0.4× 50 0.5× 45 0.8× 32 720
Aaron Klein Germany 8 753 1.8× 236 1.7× 84 0.7× 56 0.5× 129 2.4× 25 1.2k
Marius Lindauer Germany 12 492 1.2× 74 0.5× 70 0.6× 44 0.4× 149 2.8× 35 939
Samah Alshathri Saudi Arabia 17 255 0.6× 98 0.7× 118 1.0× 37 0.4× 49 0.9× 57 715
Jan N. van Rijn Netherlands 12 890 2.2× 203 1.4× 81 0.7× 60 0.6× 109 2.1× 33 1.2k

Countries citing papers authored by Chung-Chian Hsu

Since Specialization
Citations

This map shows the geographic impact of Chung-Chian Hsu'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 Chung-Chian Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chung-Chian Hsu more than expected).

Fields of papers citing papers by Chung-Chian Hsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chung-Chian Hsu. 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 Chung-Chian Hsu. The network helps show where Chung-Chian Hsu may publish in the future.

Co-authorship network of co-authors of Chung-Chian Hsu

This figure shows the co-authorship network connecting the top 25 collaborators of Chung-Chian Hsu. A scholar is included among the top collaborators of Chung-Chian Hsu 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 Chung-Chian Hsu. Chung-Chian Hsu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chang, Chunqi, Rooh Ullah Khan, Chung-Chian Hsu, et al.. (2025). Novel deep learning solutions with layered recurrent neural networks for nonlinear stiff Dahl hysteresis model in piezoelectric actuator. Neural Networks. 196. 108378–108378.
2.
Sangaiah, Arun Kumar, et al.. (2025). AutoKAN: A Federated Lightweight Anomaly Detection Framework for Securing Constrained IoT Healthcare Diabetes Monitoring Systems. IEEE Transactions on Consumer Electronics. 71(4). 11303–11314.
3.
Halim, Zahid, et al.. (2025). Multi-sensor data fusion for smart healthcare: optimizing specialty-based classification of imbalanced EMRs. Information Fusion. 125. 103503–103503. 2 indexed citations
4.
Band, Shahab S., et al.. (2024). Automatic melanoma detection using discrete cosine transform features and metadata on dermoscopic images. Journal of King Saud University - Computer and Information Sciences. 36(2). 101944–101944. 6 indexed citations
5.
Chaudhary, Naveed Ishtiaq, Chung-Chian Hsu, Khizer Mehmood, et al.. (2024). A gazelle optimization expedition for key term separated fractional nonlinear systems with application to electrically stimulated muscle modeling. Chaos Solitons & Fractals. 185. 115111–115111. 13 indexed citations
6.
Hsu, Chung-Chian, et al.. (2024). End-to-End Automation of ML Model Lifecycle Management using Machine Learning Operations Platforms. 209–210. 1 indexed citations
7.
Hsu, Chung-Chian, et al.. (2024). Decoding AI Complexity: SHAP Textual Explanations via LLM for Improved Model Transparency. 197–198. 2 indexed citations
8.
Sangaiah, Arun Kumar, et al.. (2023). Investigating Routing in the VANET Network: Review and Classification of Approaches. Algorithms. 16(8). 381–381. 10 indexed citations
9.
Ameri, Rasoul, Chung-Chian Hsu, Shahab S. Band, et al.. (2023). Forecasting PM 2.5 concentration based on integrating of CEEMDAN decomposition method with SVM and LSTM. Ecotoxicology and Environmental Safety. 266. 115572–115572. 17 indexed citations
10.
11.
Hsu, Chung-Chian, et al.. (2023). A robust approach for endotracheal tube localization in chest radiographs. Frontiers in Artificial Intelligence. 6. 1181812–1181812.
12.
Band, Shahab S., Rasoul Ameri, Tao Hai, et al.. (2022). Performance improvement of machine learning models via wavelet theory in estimating monthly river streamflow. Engineering Applications of Computational Fluid Mechanics. 16(1). 1833–1848. 37 indexed citations
13.
14.
Hsu, Chung-Chian, et al.. (2020). Multi-Label Classification of ICD Coding Using Deep Learning. 22 4. 1–6. 9 indexed citations
15.
Hsu, Chung-Chian, et al.. (2011). Improving visualization of mixed-type data with a dynamic SOM. 3. 431–435. 1 indexed citations
16.
Hsu, Chung-Chian, et al.. (2011). Apply extended self-organizing map to cluster and classify mixed-type data. Neurocomputing. 74(18). 3832–3842. 27 indexed citations
17.
18.
Chen, Chien‐Hsing & Chung-Chian Hsu. (2010). System of Boosting Voting with Multiple Learning Algorithms. Journal of Digital Information Management. 8(3). 153–159. 1 indexed citations
19.
Hsu, Chung-Chian, Chin-Long Chen, & Yu-Wei Su. (2007). Hierarchical clustering of mixed data based on distance hierarchy. Information Sciences. 177(20). 4474–4492. 71 indexed citations
20.
Hsu, Chung-Chian, et al.. (2006). GViSOM for Multivariate Mixed Data Projection and Structure Visualization. The 2006 IEEE International Joint Conference on Neural Network Proceedings. 3300–3305. 8 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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