Chenglong Wang

532 total citations
34 papers, 283 citations indexed

About

Chenglong Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Chenglong Wang has authored 34 papers receiving a total of 283 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 5 papers in Control and Systems Engineering. Recurrent topics in Chenglong Wang's work include Medical Image Segmentation Techniques (6 papers), Advanced Neural Network Applications (5 papers) and Machine Fault Diagnosis Techniques (5 papers). Chenglong Wang is often cited by papers focused on Medical Image Segmentation Techniques (6 papers), Advanced Neural Network Applications (5 papers) and Machine Fault Diagnosis Techniques (5 papers). Chenglong Wang collaborates with scholars based in China, Japan and United States. Chenglong Wang's co-authors include Alvin Cheung, Jie Nie, Shumo Chu, Rastislav Bodík, Jiabao Li, Mingxi Jiang, Likun Pan, Jinliang Li, Zhiqiang Wei and Kensaku Mori and has published in prestigious journals such as Chemical Engineering Journal, IEEE Transactions on Geoscience and Remote Sensing and IEEE Access.

In The Last Decade

Chenglong Wang

29 papers receiving 278 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chenglong Wang China 10 70 60 59 35 34 34 283
Guoxiang Tong China 11 63 0.9× 89 1.5× 107 1.8× 39 1.1× 26 0.8× 39 359
Rathiah Hashim Malaysia 7 74 1.1× 44 0.7× 73 1.2× 23 0.7× 24 0.7× 26 252
Kamel H. Rahouma Egypt 11 47 0.7× 77 1.3× 95 1.6× 32 0.9× 13 0.4× 43 290
Wenhuan Wu China 8 126 1.8× 79 1.3× 57 1.0× 32 0.9× 24 0.7× 24 306
Yan Lyu China 12 33 0.5× 54 0.9× 43 0.7× 33 0.9× 17 0.5× 23 423
Valerio Mario Salerno Italy 12 24 0.3× 97 1.6× 84 1.4× 79 2.3× 28 0.8× 23 307
Hamam Mokayed Sweden 10 111 1.6× 28 0.5× 82 1.4× 19 0.5× 13 0.4× 40 281
Ankush Ghosh India 9 41 0.6× 54 0.9× 53 0.9× 32 0.9× 22 0.6× 47 258
Peng Du China 11 129 1.8× 117 1.9× 34 0.6× 11 0.3× 29 0.9× 34 430
Bharti Khemani India 4 56 0.8× 31 0.5× 92 1.6× 19 0.5× 20 0.6× 7 305

Countries citing papers authored by Chenglong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Chenglong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chenglong Wang. 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 Chenglong Wang. The network helps show where Chenglong Wang may publish in the future.

Co-authorship network of co-authors of Chenglong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Chenglong Wang. A scholar is included among the top collaborators of Chenglong Wang 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 Chenglong Wang. Chenglong Wang 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.
Wang, Chenglong, et al.. (2024). Unknown fault detection of rolling bearings guided by global–local feature coupling. Mechanical Systems and Signal Processing. 213. 111331–111331. 7 indexed citations
2.
Luo, Ze, et al.. (2024). A two-way trust routing scheme to improve security in fog computing environment. Cluster Computing. 27(9). 13165–13185. 1 indexed citations
3.
Wang, Chenglong, et al.. (2024). Cross-domain correlation representation for new fault categories discovery in rolling bearings. Information Processing & Management. 61(3). 103659–103659. 2 indexed citations
4.
Fan, Cunhang, Jianhua Tao, Jiangyan Yi, et al.. (2024). Spatial reconstructed local attention Res2Net with F0 subband for fake speech detection. Neural Networks. 175. 106320–106320. 4 indexed citations
5.
Yan, Tao, et al.. (2024). GLGFN: Global-Local Grafting Fusion Network for High-Resolution Image Deraining. IEEE Transactions on Circuits and Systems for Video Technology. 34(11). 10860–10873. 2 indexed citations
6.
Wang, Peng, et al.. (2024). APPLICATION ANALYSIS OF PHOTOVOLTAIC INTEGRATED SHADING DEVICES CONSIDERING INDOOR ENVIRONMENT AND ENERGY CHANGE IN GREEN BUILDINGS. Journal of Green Building. 19(3). 71–90. 1 indexed citations
7.
Wang, Chenglong, et al.. (2024). Multi-Scale Permutation Entropy for Audio Deepfake Detection. 1406–1410. 10 indexed citations
8.
Nie, Jie, et al.. (2023). A Multiscale Graph Convolutional Neural Network Framework for Fault Diagnosis of Rolling Bearing. IEEE Transactions on Instrumentation and Measurement. 72. 1–13. 28 indexed citations
9.
Jiang, Mingxi, Yajuan Zhang, Zihao Yang, et al.. (2023). A data-driven interpretable method to predict capacities of metal ion doped TiO2 anode materials for lithium-ion batteries using machine learning classifiers. Inorganic Chemistry Frontiers. 10(22). 6646–6654. 22 indexed citations
10.
Wang, Zhaoxin, et al.. (2023). Statistical texture involved multi-granularity attention network for remote sensing semantic segmentation. Multimedia Tools and Applications. 83(9). 25817–25841.
11.
Xu, Jiali, et al.. (2023). Unknown fault detection method for rolling bearings based on image and signal series feature fusion enhancement. Multimedia Tools and Applications. 83(41). 89479–89500. 1 indexed citations
12.
Wang, Chenglong, Jiangyan Yi, Jianhua Tao, et al.. (2023). TO-Rawnet: Improving RawNet with TCN and Orthogonal Regularization for Fake Audio Detection. 3137–3141. 7 indexed citations
13.
Zhang, Yajuan, Mingxi Jiang, Jinliang Li, et al.. (2023). A machine learning-assisted study on organic solvents in electrolytes for expanding the electrochemical stable window of zinc-ion batteries. Chemical Engineering Journal. 476. 146676–146676. 40 indexed citations
14.
Nie, Jie, et al.. (2022). Scale–Relation Joint Decoupling Network for Remote Sensing Image Semantic Segmentation. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–12. 15 indexed citations
15.
16.
Wang, Chenglong, et al.. (2021). Global and Temporal-Frequency Attention Based Network in Audio Deepfake Detection. 58(7). 1466. 1 indexed citations
17.
Wang, Chenglong, Masahiro Oda, Yuichiro Hayashi, et al.. (2019). Tensor-cut: A tensor-based graph-cut blood vessel segmentation method and its application to renal artery segmentation. Medical Image Analysis. 60. 101623–101623. 27 indexed citations
18.
Shen, Chen, Chenglong Wang, Masahiro Oda, & Kensaku Mori. (2019). Coarse-to-fine kidney and tumor segmentation with fully convolutional networks. University of Minnesota Digital Conservancy (University of Minnesota). 2 indexed citations
19.
Chu, Shumo, et al.. (2017). Cosette: An Automated Prover for SQL.. Conference on Innovative Data Systems Research. 32 indexed citations
20.
Wang, Chenglong, et al.. (2016). Progress and prospects of border effect research. 35(9). 1118. 5 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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