Chun-Hao Yang

422 total citations
10 papers, 270 citations indexed

About

Chun-Hao Yang is a scholar working on Geometry and Topology, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Chun-Hao Yang has authored 10 papers receiving a total of 270 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Geometry and Topology, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Chun-Hao Yang's work include Morphological variations and asymmetry (2 papers), Face and Expression Recognition (2 papers) and Image Retrieval and Classification Techniques (2 papers). Chun-Hao Yang is often cited by papers focused on Morphological variations and asymmetry (2 papers), Face and Expression Recognition (2 papers) and Image Retrieval and Classification Techniques (2 papers). Chun-Hao Yang collaborates with scholars based in Taiwan, United States and Sri Lanka. Chun-Hao Yang's co-authors include B. C. Wang, Edward F. Chang, Tse‐Min Lee, Chi-Hsuan Cheng, Chen‐Hsi Chou, Chi‐Chang Lin, Ging‐Long Lin, Sheng‐Mao Chang, Kuo‐Jung Lee and James V. Zidek and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Journal of Biomedical Materials Research.

In The Last Decade

Chun-Hao Yang

9 papers receiving 255 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chun-Hao Yang Taiwan	4	122	82	71	52	46	10	270
Kyoung-Won Kim South Korea	8	19 0.2×	53 0.6×	78 1.1×	21 0.4×	7 0.2×	25	316
Wen He China	10	243 2.0×	34 0.4×	3 0.0×	36 0.7×	92 2.0×	28	399
Himanta Bansal India	7	44 0.4×	27 0.3×	3 0.0×	73 1.4×	6 0.1×	16	316
M Kovacevic Serbia	8	17 0.1×	42 0.5×	19 0.3×	3 0.1×	13 0.3×	40	157
S. M. Motzkin United States	4	75 0.6×	58 0.7×	1 0.0×	17 0.3×	110 2.4×	4	281
Huachao Liu China	11	54 0.4×	54 0.7×	11 0.2×	17 0.3×	16 0.3×	26	564
Siew Ann Tan Singapore	8	27 0.2×	17 0.2×	35 0.5×	3 0.1×	31 0.7×	10	307
Qingliang Zhao China	10	89 0.7×	27 0.3×	6 0.1×	2 0.0×	33 0.7×	33	348
Gustavo Jesús Vázquez-Zapién Mexico	10	57 0.5×	20 0.2×	3 0.0×	3 0.1×	36 0.8×	45	336

Countries citing papers authored by Chun-Hao Yang

Since Specialization

Citations

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

Fields of papers citing papers by Chun-Hao Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chun-Hao Yang. 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 Chun-Hao Yang. The network helps show where Chun-Hao Yang may publish in the future.

Co-authorship network of co-authors of Chun-Hao Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Chun-Hao Yang. A scholar is included among the top collaborators of Chun-Hao Yang 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 Chun-Hao Yang. Chun-Hao Yang 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:

10 of 10 papers shown

1.

Yang, Chun-Hao, et al.. (2023). Geometric Deep Learning for Unsupervised Registration of Diffusion Magnetic Resonance Images. Lecture notes in computer science. 13939. 563–575. 1 indexed citations

2.

Yang, Chun-Hao & Baba C. Vemuri. (2022). Nested Grassmannians for Dimensionality Reduction with Applications. PubMed. 1(IPMI 2021). 1–21.

3.

Yang, Chun-Hao, Hani Doss, & Baba C. Vemuri. (2022). An Empirical Bayes Approach to Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices. Journal of the American Statistical Association. 119(545). 259–272. 1 indexed citations

4.

Settu, Kalpana, et al.. (2019). Convolutional Equalizer - A Convolutional Approach to Equalize Input Features in Dimension. 101. 318–323. 1 indexed citations

5.

Yang, Chun-Hao, et al.. (2018). Bayesian Analysis of Accumulated Damage Models in Lumber Reliability. Technometrics. 61(2). 233–245. 3 indexed citations

6.

Chakraborty, Rudrasis, Chun-Hao Yang, Derek B. Archer, et al.. (2018). Statistical Recurrent Models on Manifold valued Data. 3 indexed citations

7.

Yang, Chun-Hao, et al.. (2017). milr: Multiple-Instance Logistic Regression with Lasso Penalty. The R Journal. 9(1). 446–446. 6 indexed citations

8.

Lin, Chi‐Chang, et al.. (2013). Story Damage Identification of Irregular Buildings Based on Earthquake Records. Earthquake Spectra. 29(3). 963–985. 11 indexed citations

9.

Cheng, Chi-Hsuan, et al.. (2004). Biowaiver extension potential to BCS Class III high solubility-low permeability drugs: bridging evidence for metformin immediate-release tablet. European Journal of Pharmaceutical Sciences. 22(4). 297–304. 109 indexed citations

10.

Wang, B. C., Tse‐Min Lee, Edward F. Chang, & Chun-Hao Yang. (1993). The shear strength and the failure mode of plasma‐sprayed hydroxyapatite coating to bone: The effect of coating thickness. Journal of Biomedical Materials Research. 27(10). 1315–1327. 135 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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