Li‐Dan Kuang

656 total citations
35 papers, 439 citations indexed

About

Li‐Dan Kuang is a scholar working on Signal Processing, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Li‐Dan Kuang has authored 35 papers receiving a total of 439 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Signal Processing, 12 papers in Cognitive Neuroscience and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Li‐Dan Kuang's work include Blind Source Separation Techniques (13 papers), Functional Brain Connectivity Studies (12 papers) and Tensor decomposition and applications (8 papers). Li‐Dan Kuang is often cited by papers focused on Blind Source Separation Techniques (13 papers), Functional Brain Connectivity Studies (12 papers) and Tensor decomposition and applications (8 papers). Li‐Dan Kuang collaborates with scholars based in China, United States and Finland. Li‐Dan Kuang's co-authors include Qiu‐Hua Lin, Xiao‐Feng Gong, Fengyu Cong, Piia Astikainen, Tapani Ristaniemi, Jianming Zhang, Vince D. Calhoun, Yufan He, Bin Zheng and Wentao Chen and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Transactions on Medical Imaging.

In The Last Decade

Li‐Dan Kuang

27 papers receiving 434 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Li‐Dan Kuang China 8 166 155 128 97 95 35 439
T. Adali United States 6 295 1.8× 33 0.2× 267 2.1× 57 0.6× 86 0.9× 21 554
Saideh Ferdowsi United Kingdom 12 160 1.0× 24 0.2× 186 1.5× 99 1.0× 94 1.0× 36 545
Ronald Phlypo France 14 456 2.7× 17 0.1× 305 2.4× 56 0.6× 181 1.9× 41 752
Yunbo Tang China 11 274 1.7× 24 0.2× 93 0.7× 53 0.5× 26 0.3× 27 434
Yoshikazu Washizawa Japan 9 151 0.9× 21 0.1× 119 0.9× 65 0.7× 7 0.1× 38 302
Ioan Buciu Romania 15 76 0.5× 17 0.1× 151 1.2× 713 7.4× 59 0.6× 37 952
Dingheng Wang China 9 91 0.5× 66 0.4× 13 0.1× 88 0.9× 21 0.2× 15 304
Kyuwan Choi Japan 9 141 0.8× 19 0.1× 105 0.8× 22 0.2× 15 0.2× 18 326
Saeid Sanei United Kingdom 12 256 1.5× 16 0.1× 202 1.6× 48 0.5× 13 0.1× 28 515
Vamsi Krishna Ithapu United States 10 54 0.3× 5 0.0× 134 1.0× 144 1.5× 55 0.6× 37 457

Countries citing papers authored by Li‐Dan Kuang

Since Specialization
Citations

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

Fields of papers citing papers by Li‐Dan Kuang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li‐Dan Kuang

This figure shows the co-authorship network connecting the top 25 collaborators of Li‐Dan Kuang. A scholar is included among the top collaborators of Li‐Dan Kuang 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 Li‐Dan Kuang. Li‐Dan Kuang 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.
Gui, Yan, Yaning Liu, Yan Chen, Li‐Dan Kuang, & Zhihua Chen. (2025). Lightweight structure-guided network with hydra interaction attention and global–local gating mechanism for high-resolution image inpainting. Expert Systems with Applications. 272. 126717–126717.
2.
Zhang, Jianming, Yufan He, Wentao Chen, Li‐Dan Kuang, & Bin Zheng. (2024). CorrFormer: Context-aware tracking with cross-correlation and transformer. Computers & Electrical Engineering. 114. 109075–109075. 34 indexed citations
3.
Kuang, Li‐Dan, Hao Zhu, Shiming He, et al.. (2024). Shift-invariant rank-(L, L, 1, 1) BTD with 3D spatial pooling and orthonormalization: Application to multi-subject fMRI data. Biomedical Signal Processing and Control. 92. 106058–106058.
4.
Lin, Qiu‐Hua, Li‐Dan Kuang, Binhua Zhao, et al.. (2024). A core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data. Biomedical Signal Processing and Control. 95. 106471–106471.
5.
Kuang, Li‐Dan, et al.. (2024). Dynamic functional network connectivity analysis in schizophrenia based on a spatiotemporal CPD framework. Journal of Neural Engineering. 21(1). 16032–16032. 2 indexed citations
6.
Wang, Tianhao, et al.. (2024). Hybrid Prompt Recommendation Explanation Generation combined with Graph Encoder. Neural Processing Letters. 56(1). 1 indexed citations
7.
Zhang, Jin, et al.. (2024). FATE: A Flexible FPGA-Based Automatic Test Equipment for Digital ICs. Electronics. 13(9). 1667–1667.
8.
Li, Weixing, Qiu‐Hua Lin, Binhua Zhao, et al.. (2023). Dynamic functional network connectivity based on spatial source phase maps of complex-valued fMRI data: Application to schizophrenia. Journal of Neuroscience Methods. 403. 110049–110049. 3 indexed citations
9.
Zhang, Jianming, et al.. (2023). Siamese Visual Tracking with Spatial-Channel Attention and Ranking Head Network. Electronics. 12(20). 4351–4351.
10.
Zhang, Jianming, Haitao Huang, Xiaokang Jin, Li‐Dan Kuang, & Jin Zhang. (2023). Siamese visual tracking based on criss-cross attention and improved head network. Multimedia Tools and Applications. 83(1). 1589–1615. 29 indexed citations
11.
Zhang, Jin, et al.. (2023). An Improved Biomimetic Olfactory Model and Its Application in Traffic Sign Recognition. Applied Sciences. 14(1). 87–87. 1 indexed citations
12.
Kuang, Li‐Dan, Qiu‐Hua Lin, Xiao‐Feng Gong, et al.. (2022). Constrained CPD of Complex-Valued Multi-Subject fMRI Data via Alternating Rank-R and Rank-1 Least Squares. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 30. 2630–2640. 2 indexed citations
13.
Kuang, Li‐Dan, Biao Wang, Qiu‐Hua Lin, et al.. (2022). An Accelerated Rank-(L,L,1,1) Block Term Decomposition Of Multi-Subject Fmri Data Under Spatial Orthonormality Constraint. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 23. 3933–3937.
14.
Zhang, Jianming, et al.. (2022). Visual Object Tracking via Cascaded RPN Fusion and Coordinate Attention. Computer Modeling in Engineering & Sciences. 132(3). 909–927. 2 indexed citations
15.
Zhang, Jianming, et al.. (2021). Siamese anchor-free object tracking with multiscale spatial attentions. Scientific Reports. 11(1). 22908–22908. 26 indexed citations
16.
Zhang, Chaoying, Qiu‐Hua Lin, Li‐Dan Kuang, et al.. (2020). Sparse representation of complex-valued fMRI data based on spatiotemporal concatenation of real and imaginary parts. Journal of Neuroscience Methods. 351. 109047–109047. 3 indexed citations
17.
Qiu, Yue, Qiu‐Hua Lin, Li‐Dan Kuang, et al.. (2019). Spatial source phase: A new feature for identifying spatial differences based on complex‐valued resting‐state fMRI data. Human Brain Mapping. 40(9). 2662–2676. 19 indexed citations
18.
Kuang, Li‐Dan, Qiu‐Hua Lin, Xiao‐Feng Gong, Fengyu Cong, & Vince D. Calhoun. (2016). An adaptive fixed-point IVA algorithm applied to multi-subject complex-valued FMRI data. 7 indexed citations
19.
Cong, Fengyu, Qiu‐Hua Lin, Li‐Dan Kuang, et al.. (2015). Tensor decomposition of EEG signals: A brief review. Journal of Neuroscience Methods. 248. 59–69. 229 indexed citations
20.
Kuang, Li‐Dan, Qingyong Deng, & Zhetao Li. (2013). New method for estimating SOC of lithium battery. Computer Engineering and Applications Journal. 49(6). 249–252. 2 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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