Yu‐Chen Hu

5.1k total citations · 1 hit paper
221 papers, 3.5k citations indexed

About

Yu‐Chen Hu is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Yu‐Chen Hu has authored 221 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 125 papers in Computer Vision and Pattern Recognition, 47 papers in Signal Processing and 46 papers in Artificial Intelligence. Recurrent topics in Yu‐Chen Hu's work include Advanced Data Compression Techniques (57 papers), Advanced Steganography and Watermarking Techniques (57 papers) and Chaos-based Image/Signal Encryption (47 papers). Yu‐Chen Hu is often cited by papers focused on Advanced Data Compression Techniques (57 papers), Advanced Steganography and Watermarking Techniques (57 papers) and Chaos-based Image/Signal Encryption (47 papers). Yu‐Chen Hu collaborates with scholars based in Taiwan, India and China. Yu‐Chen Hu's co-authors include Chin‐Chen Chang, Piyu Tsai, Hsiu‐Lien Yeh, Yogesh Kumar, Yu‐Hsiu Lin, Wu‐Lin Chen, Chia‐Chen Lin, Jun-Chou Chuang, Ashok Kumar and Ruchi Singla and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and Scientific Reports.

In The Last Decade

Yu‐Chen Hu

198 papers receiving 3.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Reversible image hiding scheme using predictive coding and histogram shifting

2008 456 citations Yu‐Chen Hu et al. profile →

Peers

Yu‐Chen Hu

CVPR

AI

SP

CNC

IS

Deepak Kumar Jain China

Santanu Chaudhury India

Sami Bourouis Saudi Arabia

Mengxing Huang China

Yi Chen China

Abdul Rehman Pakistan

Zhaoquan Gu China

Hari Mohan Pandey United Kingdom

Dawid Połap Poland

Abeer D. Algarni Saudi Arabia

Deepak Kumar Jain China

Yu‐Chen Hu

964 ×0.4

CVPR

752 ×1.4

AI

169 ×0.4

SP

307 ×0.8

CNC

409 ×1.3

IS

Citations per year, relative to Yu‐Chen Hu Yu‐Chen Hu (= 1×) peers Deepak Kumar Jain

Countries citing papers authored by Yu‐Chen Hu

Since Specialization

Citations

This map shows the geographic impact of Yu‐Chen Hu'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 Yu‐Chen Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu‐Chen Hu more than expected).

Fields of papers citing papers by Yu‐Chen Hu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu‐Chen Hu. 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 Yu‐Chen Hu. The network helps show where Yu‐Chen Hu may publish in the future.

Co-authorship network of co-authors of Yu‐Chen Hu

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Peng, Tianyi, et al.. (2025). AnalyticKWS: Towards Exemplar-Free Analytic Class Incremental Learning for Small-footprint Keyword Spotting. 14147–14158.

2.

Qin, Chengwei, et al.. (2025). Relevant or Random: Can LLMs Truly Perform Analogical Reasoning?. 23993–24010.

3.

Hu, Yu‐Chen, Zijian Chen, Xiaoyan Wu, et al.. (2025). Hypophysectomy, pituitary neuroadenolysis and pituitary radiosurgery for the treatment of refractory cancer pain: a historical review and mechanism investigation. Frontiers in Neurology. 15. 1529944–1529944. 1 indexed citations

4.

Wang, Pengxin, Xueyuan Bai, Xuecao Li, et al.. (2024). Machine learning techniques and interpretability for maize yield estimation using Time-Series images of MODIS and Multi-Source data. Computers and Electronics in Agriculture. 222. 109063–109063. 9 indexed citations

5.

Khan, Munna, et al.. (2024). Implementation of Bioelectrical Impedance Measuring Instrument Based on Embedded System. Mathematical Problems in Engineering. 2024. 1–10. 1 indexed citations

6.

Kant, Shri, et al.. (2024). An efficient sentiment analysis technique based on fine-tuned EdBERT for virtual learning environments. Multimedia Tools and Applications. 84(18). 20161–20175.

7.

Hu, Yu‐Chen, et al.. (2024). Home healthcare: particle swarm optimization for human resource planning under uncertainty. Multimedia Tools and Applications. 84(30). 36563–36596.

8.

Tanwar, Sarvesh, et al.. (2023). A comparative study on blockchain-based distributed public key infrastructure for IoT applications. Multimedia Tools and Applications. 83(12). 35471–35496. 1 indexed citations

9.

Mo, Pin‐Qiang, et al.. (2023). Discrete element modelling of thermal penetration test with heating and cooling. Computers and Geotechnics. 161. 105600–105600. 1 indexed citations

10.

Acharya, Biswaranjan, et al.. (2023). Automated Plant Recognition System with Geographical Position Selection for Medicinal Plants. SHILAP Revista de lepidopterología. 2023. 1–11. 3 indexed citations

11.

Suhasini, Avvaru N., et al.. (2022). Pixel-Boundary-Dependent Segmentation Method for Early Detection of Diabetic Retinopathy. Mathematical Problems in Engineering. 2022. 1–12. 3 indexed citations

12.

Bhardwaj, Akashdeep, Keshav Kaushik, Salil Bharany, et al.. (2022). IIoT: Traffic Data Flow Analysis and Modeling Experiment for Smart IoT Devices. Sustainability. 14(21). 14645–14645. 13 indexed citations

13.

Kumar, Ashok, et al.. (2022). A Systematic Survey on Fog and IoT Driven Healthcare: Open Challenges and Research Issues. Electronics. 11(17). 2668–2668. 17 indexed citations

14.

Chatterjee, Jyotir Moy, et al.. (2022). Optimized face-emotion learning using convolutional neural network and binary whale optimization. Multimedia Tools and Applications. 82(13). 19945–19968. 5 indexed citations

15.

Imrana, Yakubu, Yanping Xiang, Liaqat Ali, et al.. (2022). χ2-BidLSTM: A Feature Driven Intrusion Detection System Based on χ2 Statistical Model and Bidirectional LSTM. Sensors. 22(5). 2018–2018. 23 indexed citations

16.

Liu, Jain‐Shing, Chun‐Hung Richard Lin, & Yu‐Chen Hu. (2020). Joint Resource Allocation, User Association, and Power Control for 5G LTE-Based Heterogeneous Networks. IEEE Access. 8. 122654–122672. 22 indexed citations

17.

Chen, Yu, et al.. (2020). Low-Computation-Cost Data Hiding Scheme Based on Turtle Shell.. Int. J. Netw. Secur.. 22. 296–305. 1 indexed citations

18.

Chen, Yung-Yao, et al.. (2020). An Image Authentication Method for Secure Internet-Based Communication in Human-Centric Computing. 網際網路技術學刊. 21(7). 1893–1903.

19.

Chen, Yu, et al.. (2019). Reversible Data Hiding in Encrypted Images Based on Bit-plane Block Embedding.. J. Inf. Hiding Multim. Signal Process.. 10. 408–421. 3 indexed citations

20.

Chan, Yung‐Kuan, Wen-Chuan Wu, & Yu‐Chen Hu. (2004). Public-Key Inter-Block Dependence Fragile Watermarking for Image Authentication Using Continued Fraction.. Informatica (slovenia). 28. 147–152. 3 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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