Jia-Lien Hsu

655 total citations
36 papers, 412 citations indexed

About

Jia-Lien Hsu is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Jia-Lien Hsu has authored 36 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 17 papers in Signal Processing and 12 papers in Artificial Intelligence. Recurrent topics in Jia-Lien Hsu's work include Music and Audio Processing (14 papers), Music Technology and Sound Studies (9 papers) and Video Analysis and Summarization (8 papers). Jia-Lien Hsu is often cited by papers focused on Music and Audio Processing (14 papers), Music Technology and Sound Studies (9 papers) and Video Analysis and Summarization (8 papers). Jia-Lien Hsu collaborates with scholars based in Taiwan, Australia and China. Jia-Lien Hsu's co-authors include Chih‐Chin Liu, Arbee L. P. Chen, A.L.P. Chen, Tzu‐Chieh Lin, Hungyen Lin, Yi-Nuo Shih, Chia‐Chun Wu, Melissa H. Chang, Wen-Shuo Wu and Yikai Liao and has published in prestigious journals such as Sensors, Knowledge-Based Systems and Applied Sciences.

In The Last Decade

Jia-Lien Hsu

33 papers receiving 380 citations

Peers

Countries citing papers authored by Jia-Lien Hsu

Since Specialization

Citations

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

Fields of papers citing papers by Jia-Lien Hsu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jia-Lien Hsu

This figure shows the co-authorship network connecting the top 25 collaborators of Jia-Lien Hsu. A scholar is included among the top collaborators of Jia-Lien 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 Jia-Lien Hsu. Jia-Lien Hsu 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

#	Work	Indexed citations
1	A Social Network Analysis on the Danmaku of English-Learning Programs 2025 ·Applied Sciences ·(unknown), Xin Huang, Jia-Lien Hsu, (unknown)	1
2	Enhancing Medical Diagnosis Document Analysis with Layout-Aware Multitask Models 2025 ·Diagnostics ·(unknown), Jia-Lien Hsu	0
3	Applying a Deep Learning Model for Total Kidney Volume Measurement in Autosomal Dominant Polycystic Kidney Disease 2024 ·Bioengineering ·Jia-Lien Hsu, (unknown), (unknown), Zhilin Li, (unknown), Wen‐Shuo Wu, Tze‐Wah Kao, Pei‐Lun Chu	1
4	Calculating the distance between languages with deep learning 2023 ·Biomedical Signal Processing and Control ·(unknown), (unknown), Jia-Lien Hsu	1
5	Factors Associated with the Patient/Client Use of Report Cards, Physician Rating Websites, Social Media, and Google for Hospital and Physician Selection: A Nationwide Survey 2022 ·Healthcare ·(unknown), Chyi‐In Wu, (unknown), Jia-Lien Hsu, (unknown), Ya-Seng Hsueh, Wei‐Chih Su	1
6	Channel–Spatial Segmentation Network for Classifying Leaf Diseases 2022 ·Agriculture ·(unknown), (unknown), Jia-Lien Hsu, Yi‐Hsien Lin, Baiying Lei, Chuan-Ming Liu	6
7	Breast cancer recurrence prediction with ensemble methods and cost-sensitive learning 2021 ·Open Medicine ·(unknown), Wen-Shuo Wu, Chia‐Chun Wu, Yi-Nuo Shih, (unknown), Jia-Lien Hsu	22
8	Predicting ICD-9 Codes Using Self-Report of Patients 2021 ·Applied Sciences ·(unknown), (unknown), Yikai Liao, Jia-Lien Hsu	7
9	Development of an iPad-based assessment tool for measuring attention and validation in older employees 2020 ·Work ·Yi-Nuo Shih, Jia-Lien Hsu, (unknown), (unknown)	1
10	Digitizing abdominal palpation with a pressure measurement and positioning device 2020 ·PeerJ ·Jia-Lien Hsu, (unknown), (unknown)	5
11	Applying Under-Sampling Techniques and Cost-Sensitive Learning Methods on Risk Assessment of Breast Cancer 2015 ·Journal of Medical Systems ·Jia-Lien Hsu, (unknown), Hungyen Lin, (unknown)	29
12	A Hybrid Method for Sequence Clustering 2014 ·Journal of information science and engineering ·Jia-Lien Hsu, (unknown), I‐Chin Wu	0
13	An entropy-based query expansion approach for learning researchers’ dynamic information needs 2013 ·Knowledge-Based Systems ·I‐Chin Wu, Guan‐Wei Chen, Jia-Lien Hsu, Chunyu Lin	2
14	An Automaton-Based Filtering System for Streaming MusicXML. 2006 ·(unknown), Jia-Lien Hsu	1
15	MF-tree: Extracting and Clustering the Structural Features from Music Object in MusicXML. 2006 ·Yu‐Chih Shen, Jia-Lien Hsu, (unknown)	1
16	Finding Approximate Repeating Patterns From Sequence Data. 2004 ·Zenodo (CERN European Organization for Nuclear Research) ·Jia-Lien Hsu, Arbee L. P. Chen, (unknown)	4
17	The effectiveness study of various music information retrieval approaches 2002 ·Jia-Lien Hsu, Arbee L. P. Chen, (unknown), (unknown)	1
18	Query by music segments: an efficient approach for song retrieval 2002 ·A.L.P. Chen, Melissa H. Chang, (unknown), Jia-Lien Hsu, (unknown), (unknown)	29
19	Efficient Near Neighbor Searching Using Multi-Indexes for Content-Based Multimedia Data Retrieval 2001 ·Multimedia Tools and Applications ·(unknown), Jia-Lien Hsu, Arbee L. P. Chen	4
20	Efficient repeating pattern finding in music databases 1998 ·Jia-Lien Hsu, Arbee L. P. Chen, (unknown)	53

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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