Sheng-Chih Yang

405 total citations
36 papers, 294 citations indexed

About

Sheng-Chih Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Sheng-Chih Yang has authored 36 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 7 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Sheng-Chih Yang's work include AI in cancer detection (7 papers), Medical Image Segmentation Techniques (6 papers) and Image Retrieval and Classification Techniques (5 papers). Sheng-Chih Yang is often cited by papers focused on AI in cancer detection (7 papers), Medical Image Segmentation Techniques (6 papers) and Image Retrieval and Classification Techniques (5 papers). Sheng-Chih Yang collaborates with scholars based in Taiwan, United States and China. Sheng-Chih Yang's co-authors include Chuin-Mu Wang, Pau‐Choo Chung, Chenhui Yang, Yi Ding, Yang Gu, Dmitry A. Rodionov, Weihong Jiang, Weiwen Zhang, Cong Ren and Zhe Sun and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Medical Imaging and IEEE Transactions on Vehicular Technology.

In The Last Decade

Sheng-Chih Yang

33 papers receiving 279 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sheng-Chih Yang Taiwan 8 78 77 72 50 39 36 294
Tengfei Yin China 6 42 0.5× 56 0.7× 52 0.7× 28 0.6× 8 0.2× 7 288
Jatinder Manhas India 12 50 0.6× 69 0.9× 40 0.6× 186 3.7× 30 0.8× 32 475
Shoffan Saifullah Indonesia 14 30 0.4× 109 1.4× 24 0.3× 185 3.7× 79 2.0× 70 509
Riries Rulaningtyas Indonesia 11 21 0.3× 119 1.5× 45 0.6× 104 2.1× 30 0.8× 77 372
Karun Verma India 10 45 0.6× 126 1.6× 52 0.7× 54 1.1× 6 0.2× 26 366
Abhinav Juneja India 10 20 0.3× 35 0.5× 14 0.2× 61 1.2× 18 0.5× 23 225
V. Balamurugan India 11 12 0.2× 79 1.0× 22 0.3× 46 0.9× 20 0.5× 47 284
Samreen Naeem Pakistan 10 20 0.3× 39 0.5× 40 0.6× 93 1.9× 28 0.7× 26 434
Wataru Shimoda Japan 10 20 0.3× 267 3.5× 101 1.4× 169 3.4× 17 0.4× 28 480

Countries citing papers authored by Sheng-Chih Yang

Since Specialization
Citations

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

Fields of papers citing papers by Sheng-Chih Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheng-Chih Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Sheng-Chih Yang. A scholar is included among the top collaborators of Sheng-Chih 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 Sheng-Chih Yang. Sheng-Chih Yang 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.
Yang, Sheng-Chih, et al.. (2024). Developing a system for the real-time collection and analysis of mobile vehicle emission data. Results in Engineering. 23. 102706–102706.
2.
Joyce, Mary Kate P., Sheng-Chih Yang, Karen H. Morin, et al.. (2024). β1-adrenoceptor expression on GABAergic interneurons in primate dorsolateral prefrontal cortex: potential role in stress-induced cognitive dysfunction. Neurobiology of Stress. 30. 100628–100628. 5 indexed citations
3.
Kuo, Hsion-Wen, Wen‐Dar Lin, Chenwei Li, et al.. (2021). From simple and specific zymographic detections to the annotation of a fungus Daldinia caldariorum D263 that encodes a wide range of highly bioactive cellulolytic enzymes. Biotechnology for Biofuels. 14(1). 120–120. 4 indexed citations
4.
Yang, Sheng-Chih, et al.. (2020). A Big Data-Based Target Cost Management System. 20. 308–311.
5.
Yang, Sheng-Chih, et al.. (2017). Foreground detection using texture-based codebook method for monitoring systems. Signal Image and Video Processing. 12(4). 693–701. 2 indexed citations
6.
Yang, Sheng-Chih, et al.. (2016). Image Backlight Compensation Using Recurrent Functional Neural Fuzzy Networks Based on Modified Differential Evolution. Iranian journal of fuzzy systems. 13(6). 1–19. 3 indexed citations
7.
Yang, Sheng-Chih. (2016). A robust approach for subject segmentation of medical Images: Illustration with mammograms and breast magnetic resonance images. Computers & Electrical Engineering. 62. 151–165. 10 indexed citations
8.
Yang, Sheng-Chih, et al.. (2016). Breast MRIs Reporting Aided System. 1063–1066. 1 indexed citations
9.
Yang, Sheng-Chih, et al.. (2015). Reconstruction of three-dimensional breast-tumor model using multispectral gradient vector flow snake method. Journal of Applied Research and Technology. 13(2). 279–290. 5 indexed citations
10.
Huang, Chun‐Ying, et al.. (2014). An integrated DEA-MODM methodology for portfolio optimization. Operational Research. 15(1). 115–136. 28 indexed citations
11.
Yang, Sheng-Chih, et al.. (2014). Eight-Scale Image Contrast Enhancement Based on Adaptive Inverse Hyperbolic Tangent Algorithm. Algorithms. 7(4). 597–607. 6 indexed citations
12.
Gu, Yang, Yi Ding, Cong Ren, et al.. (2010). Reconstruction of xylose utilization pathway and regulons in Firmicutes. BMC Genomics. 11(1). 255–255. 102 indexed citations
13.
Wang, Chuin-Mu, Tsung‐Hung Lin, Ruey‐Maw Chen, & Sheng-Chih Yang. (2010). APPLICATION OF GRAY SYSTEM THEORY IN MRI CLASSIFICATION. Biomedical Engineering Applications Basis and Communications. 22(2). 111–118. 1 indexed citations
14.
Yang, Sheng-Chih, Chuin-Mu Wang, Hsian‐He Hsu, et al.. (2009). Contrast enhancement and tissues classification of breast MRI using Kalman filter-based linear mixing method. Computerized Medical Imaging and Graphics. 33(3). 187–196. 9 indexed citations
15.
Wang, Chuin-Mu, et al.. (2006). An Extenics Approach to MRI Classification. 1. 562–567. 2 indexed citations
16.
Chung, Pau‐Choo, Chuin-Mu Wang, Sheng-Chih Yang, & Hsian‐He Hsu. (2006). Tissues Classification for Breast MRI Contrast Enhancement Using Spectral Signature Detection Approach. 12. 3917–3921. 1 indexed citations
17.
Yang, Sheng-Chih, Hsian‐He Hsu, Giu‐Cheng Hsu, et al.. (2005). 3D localization of clustered microcalcifications using cranio-caudal and medio-lateral oblique views. Computerized Medical Imaging and Graphics. 29(7). 521–532. 7 indexed citations
18.
Wang, Su, Che-Wei Chang, Sheng-Chih Yang, et al.. (2005). 3D ROC Analysis for Medical Imaging Diagnosis. PubMed. 2005. 7545–7548. 10 indexed citations
19.
Wang, Chuin-Mu, Clayton Chi‐Chang Chen, Sheng-Chih Yang, et al.. (2003). Detection of spectral signatures in multispectral MR images for classification. IEEE Transactions on Medical Imaging. 22(1). 50–61. 32 indexed citations
20.
Yang, Sheng-Chih & Hon‐Man Liu. (1996). MR imaging of a multiple component craniocervical neurenteric cyst. European Journal of Radiology. 22(2). 138–140. 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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