Ching-Hsiang Yang

512 total citations
10 papers, 393 citations indexed

About

Ching-Hsiang Yang is a scholar working on Cognitive Neuroscience, Automotive Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ching-Hsiang Yang has authored 10 papers receiving a total of 393 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cognitive Neuroscience, 3 papers in Automotive Engineering and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Ching-Hsiang Yang's work include Tactile and Sensory Interactions (4 papers), Smart Parking Systems Research (3 papers) and Autonomous Vehicle Technology and Safety (3 papers). Ching-Hsiang Yang is often cited by papers focused on Tactile and Sensory Interactions (4 papers), Smart Parking Systems Research (3 papers) and Autonomous Vehicle Technology and Safety (3 papers). Ching-Hsiang Yang collaborates with scholars based in Taiwan and Japan. Ching-Hsiang Yang's co-authors include Liang-Bi Chen, Wan‐Jung Chang, Jian-Ping Su, C.C. Chang, Toshikazu Suzuki, Kiyomi Hamaguchi, Kunihiko Hayashi, Kiyoshi Ikeda, Chia-Hao Hsu and Cheng‐Hsin Chuang and has published in prestigious journals such as IEEE Sensors Journal, IEEE Transactions on Consumer Electronics and Biochimica et Biophysica Acta (BBA) - Protein Structure.

In The Last Decade

Ching-Hsiang Yang

9 papers receiving 338 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ching-Hsiang Yang Taiwan	7	179	159	100	83	42	10	393
Antoine Marin France	13	355 2.0×	31 0.2×	33 0.3×	46 0.6×	8 0.2×	20	631
Maximilian Schmidt Germany	13	254 1.4×	54 0.3×	257 2.6×	20 0.2×	6 0.1×	21	840
Hesheng Zhang China	12	168 0.9×	34 0.2×	26 0.3×	45 0.5×	6 0.1×	54	518
Peter Sykacek Austria	14	292 1.6×	34 0.2×	197 2.0×	21 0.3×	3 0.1×	36	827
Junru Li China	15	149 0.8×	22 0.1×	171 1.7×	162 2.0×	1 0.0×	62	766
Yuta Nishiyama Japan	9	61 0.3×	20 0.1×	38 0.4×	21 0.3×	16 0.4×	35	320
Pieter Coussement Belgium	11	281 1.6×	48 0.3×	104 1.0×	50 0.6×	2 0.0×	22	443
Chih-Pin Hsiao United States	12	167 0.9×	35 0.2×	63 0.6×	64 0.8×	6 0.1×	19	436
Hongyi Li China	14	182 1.0×	28 0.2×	52 0.5×	7 0.1×		36	743
Francisco Altimiras Chile	10	70 0.4×	76 0.5×	62 0.6×	7 0.1×	23 0.5×	12	279

Countries citing papers authored by Ching-Hsiang Yang

Since Specialization

Citations

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

Fields of papers citing papers by Ching-Hsiang Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ching-Hsiang Yang

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

Chang, Wan‐Jung, Jian-Ping Su, Liang-Bi Chen, et al.. (2020). An AI Edge Computing Based W earable Assistive Device for Visually Impaired People Zebra-Crossing Walking. 1–2. 9 indexed citations

2.

Chang, Wan‐Jung, et al.. (2020). An Artificial Intelligence Edge Computing-Based Assistive System for Visually Impaired Pedestrian Safety at Zebra Crossings. IEEE Transactions on Consumer Electronics. 67(1). 3–11. 46 indexed citations

3.

Chang, Wan‐Jung, et al.. (2020). An Intelligent Maintenance and Repair Informing System Using Machine Learning Techniques for Solar Power Generation Equipment. 1–2. 1 indexed citations

4.

Chang, Wan‐Jung, et al.. (2020). Design and Implementation of an Intelligent Assistive System for Visually Impaired People for Aerial Obstacle Avoidance and Fall Detection. IEEE Sensors Journal. 20(17). 10199–10210. 68 indexed citations

5.

Liu, Shangwei, et al.. (2020). 3D Cameras and Algorithms for Multi-Angle Gripping and Control of Robotic Arm. 363–365. 1 indexed citations

6.

Chen, Liang-Bi, et al.. (2019). An Implementation of an Intelligent Assistance System for Visually Impaired/Blind People. 1–2. 45 indexed citations

7.

Yang, Ching-Hsiang, et al.. (1969). The amino acid sequence of cobrotoxin. Biochimica et Biophysica Acta (BBA) - Protein Structure. 188(1). 65–77. 123 indexed citations

8.

Yang, Ching-Hsiang, C.C. Chang, Kunihiko Hayashi, et al.. (1968). Optical rotatory dispersion and circular dichroism of cobrotoxin. Biochimica et Biophysica Acta (BBA) - Protein Structure. 168(2). 373–376. 42 indexed citations

9.

Yang, Ching-Hsiang. (1967). The disulfide bonds of cobrotoxin and their relationship to lethality. Biochimica et Biophysica Acta (BBA) - Protein Structure. 133(2). 346–355. 54 indexed citations

10.

Yang, Ching-Hsiang, et al.. (1967). Studies on fluorescent cobrotoxin. Biochimica et Biophysica Acta (BBA) - Protein Structure. 147(3). 600–602. 4 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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