Ting‐Li Chen

1.1k total citations
41 papers, 286 citations indexed

About

Ting‐Li Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Statistics and Probability. According to data from OpenAlex, Ting‐Li Chen has authored 41 papers receiving a total of 286 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 10 papers in Statistics and Probability. Recurrent topics in Ting‐Li Chen's work include Retinal Imaging and Analysis (7 papers), Image and Signal Denoising Methods (6 papers) and Markov Chains and Monte Carlo Methods (5 papers). Ting‐Li Chen is often cited by papers focused on Retinal Imaging and Analysis (7 papers), Image and Signal Denoising Methods (6 papers) and Markov Chains and Monte Carlo Methods (5 papers). Ting‐Li Chen collaborates with scholars based in Taiwan, China and United States. Ting‐Li Chen's co-authors include Stuart Geman, David L. Sheinberg, Chii-Ruey Hwang, Matthew Tom Harrison, Asohan Amarasingham, Bin Sheng, Xiaohong Liu, Xiaoer Wei, Fushing Hsieh and Menghan Hu and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and IEEE Transactions on Information Theory.

In The Last Decade

Ting‐Li Chen

37 papers receiving 276 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ting‐Li Chen Taiwan 10 85 61 58 36 31 41 286
Firdaus Janoos United States 12 99 1.2× 41 0.7× 110 1.9× 15 0.4× 64 2.1× 32 351
Roman Sandler United States 11 114 1.3× 72 1.2× 49 0.8× 4 0.1× 16 0.5× 18 297
Xiaohui Xie United States 9 54 0.6× 121 2.0× 104 1.8× 42 1.2× 20 0.6× 12 358
Sarang Joshi United States 7 187 2.2× 43 0.7× 65 1.1× 21 0.6× 82 2.6× 17 372
N. Suzumura Japan 11 53 0.6× 56 0.9× 47 0.8× 9 0.3× 54 1.7× 37 353
Dhirendra Kumar India 10 174 2.0× 28 0.5× 117 2.0× 9 0.3× 23 0.7× 27 333
Hani Hamdan France 9 20 0.2× 102 1.7× 73 1.3× 7 0.2× 12 0.4× 30 309
Rasmus Elsborg Madsen Denmark 8 48 0.6× 153 2.5× 167 2.9× 15 0.4× 5 0.2× 16 394
Imtiaz Ahmed Awan Pakistan 11 98 1.2× 82 1.3× 193 3.3× 7 0.2× 93 3.0× 18 455
Liangjia Zhu United States 11 173 2.0× 16 0.3× 54 0.9× 5 0.1× 115 3.7× 33 394

Countries citing papers authored by Ting‐Li Chen

Since Specialization
Citations

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

Fields of papers citing papers by Ting‐Li Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ting‐Li Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Ting‐Li Chen. A scholar is included among the top collaborators of Ting‐Li Chen 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 Ting‐Li Chen. Ting‐Li Chen 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.
Zhang, Chenxi, Zhouyu Guan, Ting‐Li Chen, et al.. (2024). AI-enhanced digital technologies for myopia management: advancements, challenges, and future prospects. The Visual Computer. 40(6). 3871–3887. 10 indexed citations
2.
Liu, Xiaohong, et al.. (2023). TransMRSR: transformer-based self-distilled generative prior for brain MRI super-resolution. The Visual Computer. 39(8). 3647–3659. 51 indexed citations
3.
Hsieh, Fushing, et al.. (2023). Multiscale major factor selections for complex system data with structural dependency and heterogeneity. Physica A Statistical Mechanics and its Applications. 630. 129227–129227. 2 indexed citations
4.
5.
Liao, Min‐Tsun, et al.. (2023). Few-shot transfer learning for personalized atrial fibrillation detection using patient-based siamese network with single-lead ECG records. Artificial Intelligence in Medicine. 144. 102644–102644. 16 indexed citations
6.
Wen, Yang, et al.. (2023). Attention-based multi-scale feature fusion network for myopia grading using optical coherence tomography images. The Visual Computer. 40(9). 6627–6638. 10 indexed citations
7.
8.
Yang, Hao, et al.. (2022). Gender-Specific Impact of Metabolic Obesity Phenotypes on the Risk of Hashimoto’s Thyroiditis: A Retrospective Data Analysis Using a Health Check-Up Database. Dove Medical Press (Taylor and Francis Group). 11 indexed citations
9.
Chen, Ting‐Li, et al.. (2022). Unraveling Hidden Major Factors by Breaking Heterogeneity into Homogeneous Parts within Many-System Problems. Entropy. 24(2). 170–170. 4 indexed citations
10.
Zhang, Xiaohong, et al.. (2022). Clinical effect of methimazole combined with selenium in the treatment of toxic diffuse goiter in children. World Journal of Clinical Cases. 10(4). 1190–1197. 1 indexed citations
11.
Hsieh, Fushing, et al.. (2021). Mimicking Complexity of Structured Data Matrix’s Information Content: Categorical Exploratory Data Analysis. Entropy. 23(5). 594–594. 6 indexed citations
12.
Chen, Ting‐Li, et al.. (2021). Categorical Nature of Major Factor Selection via Information Theoretic Measurements. Entropy. 23(12). 1684–1684. 6 indexed citations
13.
Chen, Ting‐Li, et al.. (2020). A preliminary study of a deep learning assisted diagnostic system with an artificial intelligence for detection of retina disease. SHILAP Revista de lepidopterología. 1 indexed citations
14.
Chen, Ting‐Li, Hironori Fujisawa, Su‐Yun Huang, & Chii-Ruey Hwang. (2015). On the weak convergence and Central Limit Theorem of blurring and nonblurring processes with application to robust location estimation. Journal of Multivariate Analysis. 143. 165–184. 1 indexed citations
15.
Chen, Ting‐Li, et al.. (2014). An Introduction to Multilinear Principal Component Analysis. 52(1). 24–43. 2 indexed citations
16.
Chen, Ting‐Li. (2013). Optimal Markov chain Monte Carlo sampling. Wiley Interdisciplinary Reviews Computational Statistics. 5(5). 341–348. 1 indexed citations
17.
Chen, Ting‐Li, et al.. (2012). A clustering algorithm by self-updating process. arXiv (Cornell University). 3 indexed citations
18.
Chen, Ting‐Li, et al.. (2012). On the Optimal Transition Matrix for Markov Chain Monte Carlo Sampling. SIAM Journal on Control and Optimization. 50(5). 2743–2762. 9 indexed citations
19.
Yu, Hon‐Tsen, Gwo‐Chin Ma, Shih‐Chien Chin, et al.. (2011). Use of a cytogenetic whole-genome comparison to resolve phylogenetic relationships among three species: Implications for mammalian systematics and conservation biology. Theriogenology. 77(8). 1615–1623. 4 indexed citations
20.
Amarasingham, Asohan, Ting‐Li Chen, Stuart Geman, Matthew Tom Harrison, & David L. Sheinberg. (2006). Spike Count Reliability and the Poisson Hypothesis. Journal of Neuroscience. 26(3). 801–809. 53 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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