Shanshan Ji

809 total citations · 2 hit papers
20 papers, 640 citations indexed

About

Shanshan Ji is a scholar working on Control and Systems Engineering, Mechanical Engineering and Aerospace Engineering. According to data from OpenAlex, Shanshan Ji has authored 20 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Control and Systems Engineering, 10 papers in Mechanical Engineering and 6 papers in Aerospace Engineering. Recurrent topics in Shanshan Ji's work include Machine Fault Diagnosis Techniques (13 papers), Gear and Bearing Dynamics Analysis (10 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (6 papers). Shanshan Ji is often cited by papers focused on Machine Fault Diagnosis Techniques (13 papers), Gear and Bearing Dynamics Analysis (10 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (6 papers). Shanshan Ji collaborates with scholars based in China and Singapore. Shanshan Ji's co-authors include Jinrui Wang, Baokun Han, Xingxing Jiang, Huaiqian Bao, Shunming Li, Zenghui An, Weiwei Qian, Zongzhen Zhang, Zhiliang Liu and Haiyan Jin and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and Remote Sensing.

In The Last Decade

Shanshan Ji

18 papers receiving 611 citations

Hit Papers

Batch-normalized deep neural networks for achieving fast ... 2018 2026 2020 2023 2018 2023 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Batch-normalized deep neural networks for achieving fast intelligent fault diagnosis of machines
    2018 219 citations Jinrui Wang, Shunming Li et al. Neurocomputing profile →
  2. Digital twin aided adversarial transfer learning method for domain adaptation fault diagnosis
    2023 110 citations Jinrui Wang, Zongzhen Zhang et al. Reliability Engineering & System Safety profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shanshan Ji China 10 469 292 146 87 53 20 640
Dhiraj Neupane South Korea 8 401 0.9× 260 0.9× 120 0.8× 78 0.9× 40 0.8× 10 621
Jiande Wu China 13 419 0.9× 306 1.0× 136 0.9× 68 0.8× 50 0.9× 90 604
Rongzhen Zhao China 14 361 0.8× 220 0.8× 115 0.8× 77 0.9× 64 1.2× 39 489
Jongwon Seok South Korea 9 370 0.8× 254 0.9× 113 0.8× 86 1.0× 37 0.7× 28 653
Han Cheng China 9 403 0.9× 262 0.9× 89 0.6× 93 1.1× 45 0.8× 21 593
Mohd Syahril Ramadhan Mohd Saufi Malaysia 8 455 1.0× 267 0.9× 128 0.9× 87 1.0× 48 0.9× 22 584
Chenyu Liu China 11 368 0.8× 242 0.8× 108 0.7× 107 1.2× 62 1.2× 32 547
Qinghua Zhang China 12 567 1.2× 301 1.0× 198 1.4× 101 1.2× 67 1.3× 44 728

Countries citing papers authored by Shanshan Ji

Since Specialization
Citations

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

Fields of papers citing papers by Shanshan Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanshan Ji

This figure shows the co-authorship network connecting the top 25 collaborators of Shanshan Ji. A scholar is included among the top collaborators of Shanshan Ji 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 Shanshan Ji. Shanshan Ji 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, Wei, et al.. (2024). A Lightweight Riemannian Covariance Matrix Convolutional Network for PolSAR Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–17. 6 indexed citations
2.
3.
Ji, Shanshan, et al.. (2024). Content-Adaptive Multi-Region Deep Network for Polarimetric SAR Image Classification. IEEE Transactions on Circuits and Systems for Video Technology. 35(1). 617–631. 6 indexed citations
4.
Wang, Jinrui, Zongzhen Zhang, Zhiliang Liu, et al.. (2023). Digital twin aided adversarial transfer learning method for domain adaptation fault diagnosis. Reliability Engineering & System Safety. 234. 109152–109152. 110 indexed citations breakdown →
5.
6.
Han, Rui, et al.. (2023). Attention mechanism guided sparse filtering for mechanical intelligent fault diagnosis under variable speed condition. Measurement Science and Technology. 35(4). 42001–42001. 8 indexed citations
7.
Jin, Haiyan, et al.. (2023). Combine Superpixel-Wise GCN and Pixel-Wise CNN for Polsar Image Classification. 8014–8017. 8 indexed citations
8.
Ji, Shanshan, et al.. (2023). CNN-Improved Superpixel-to-Pixel Fuzzy Graph Convolution Network for PolSAR Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–18. 17 indexed citations
9.
Ji, Shanshan, Jinrui Wang, Baokun Han, et al.. (2022). Weak fault diagnosis of machinery using Laplacian eigenmaps and parallel sparse filtering. Measurement Science and Technology. 33(11). 114003–114003. 5 indexed citations
10.
Bao, Huaiqian, Shanshan Ji, Jinrui Wang, et al.. (2021). An enhanced sparse filtering method for transfer fault diagnosis using maximum classifier discrepancy. Measurement Science and Technology. 32(8). 85105–85105. 31 indexed citations
11.
Ji, Shanshan, Baokun Han, Zongzhen Zhang, et al.. (2021). Parallel sparse filtering for intelligent fault diagnosis using acoustic signal processing. Neurocomputing. 462. 466–477. 36 indexed citations
12.
Ji, Shanshan, et al.. (2021). A Generalizable Sample Resolution Augmentation Method for Mechanical Fault Diagnosis Based on ESPCN. Journal of Sensors. 2021(1). 3 indexed citations
13.
Zhang, Guowei, Shanshan Ji, Baokun Han, & Sixiang Jia. (2020). An Intelligent Diagnosis Method of Bearing Fault Based on Acoustic Signal Processing. 137–140.
14.
Wang, Jinrui, Shanshan Ji, Baokun Han, & Huaiqian Bao. (2020). Intelligent fault diagnosis for rotating machinery using L1/2-SF under variable rotational speed. Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering. 235(5). 1409–1422. 13 indexed citations
15.
Wang, Jinrui, Shanshan Ji, Baokun Han, Huaiqian Bao, & Xingxing Jiang. (2020). Deep Adaptive Adversarial Network-Based Method for Mechanical Fault Diagnosis under Different Working Conditions. Complexity. 2020. 1–11. 22 indexed citations
16.
Han, Baokun, Shanshan Ji, Jinrui Wang, Huaiqian Bao, & Xingxing Jiang. (2020). An intelligent diagnosis framework for roller bearing fault under speed fluctuation condition. Neurocomputing. 420. 171–180. 70 indexed citations
17.
18.
Wang, Jiening, et al.. (2019). Study on human error in AIDC transfer based on STPA and fuzzy BN. Zhongguo anquan kexue xuebao. 29(9). 27. 1 indexed citations
19.
Wang, Jinrui, Shunming Li, Baokun Han, et al.. (2019). Generalization of Deep Neural Networks for Imbalanced Fault Classification of Machinery Using Generative Adversarial Networks. IEEE Access. 7. 111168–111180. 70 indexed citations
20.
Wang, Jinrui, Shunming Li, Zenghui An, et al.. (2018). Batch-normalized deep neural networks for achieving fast intelligent fault diagnosis of machines. Neurocomputing. 329. 53–65. 219 indexed citations breakdown →

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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