Zhao Lv

1.4k total citations · 1 hit paper
85 papers, 888 citations indexed

About

Zhao Lv is a scholar working on Cognitive Neuroscience, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Zhao Lv has authored 85 papers receiving a total of 888 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Cognitive Neuroscience, 29 papers in Signal Processing and 21 papers in Artificial Intelligence. Recurrent topics in Zhao Lv's work include EEG and Brain-Computer Interfaces (38 papers), Blind Source Separation Techniques (20 papers) and Gaze Tracking and Assistive Technology (19 papers). Zhao Lv is often cited by papers focused on EEG and Brain-Computer Interfaces (38 papers), Blind Source Separation Techniques (20 papers) and Gaze Tracking and Assistive Technology (19 papers). Zhao Lv collaborates with scholars based in China, United States and Singapore. Zhao Lv's co-authors include Xiaopei Wu, Cunhang Fan, Mi Li, Lei Zhang, Dexiang Zhang, Taihao Li, Chao Zhang, Jianhua Tao, Xiangping Gao and Shiang Hu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and NeuroImage.

In The Last Decade

Zhao Lv

70 papers receiving 859 citations

Hit Papers

Light-weight residual convolution-based capsule network f... 2024 2026 2025 2024 10 20 30 40
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. Light-weight residual convolution-based capsule network for EEG emotion recognition
    2024 41 citations Cunhang Fan, Taihao Li et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhao Lv China 17 526 255 201 170 152 85 888
Yunyuan Gao China 17 636 1.2× 101 0.4× 180 0.9× 153 0.9× 123 0.8× 59 898
Brent J. Lance United States 19 749 1.4× 224 0.9× 173 0.9× 144 0.8× 128 0.8× 38 1.0k
Yuliang Ma China 18 527 1.0× 85 0.3× 282 1.4× 118 0.7× 150 1.0× 51 840
Yonghao Song China 14 566 1.1× 145 0.6× 97 0.5× 122 0.7× 186 1.2× 29 797
Theerawit Wilaiprasitporn Thailand 16 740 1.4× 154 0.6× 178 0.9× 167 1.0× 76 0.5× 56 1.1k
Sachin Taran India 14 582 1.1× 120 0.5× 157 0.8× 229 1.3× 95 0.6× 38 846
Jianhai Zhang China 19 922 1.8× 197 0.8× 516 2.6× 164 1.0× 180 1.2× 75 1.4k
Setha Pan-ngum Thailand 11 732 1.4× 110 0.4× 410 2.0× 143 0.8× 86 0.6× 30 945
Tohid Yousefi Rezaii Iran 16 405 0.8× 65 0.3× 179 0.9× 152 0.9× 117 0.8× 57 762
Shuang Qiu China 18 1.1k 2.0× 235 0.9× 396 2.0× 176 1.0× 168 1.1× 53 1.4k

Countries citing papers authored by Zhao Lv

Since Specialization
Citations

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

Fields of papers citing papers by Zhao Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhao Lv

This figure shows the co-authorship network connecting the top 25 collaborators of Zhao Lv. A scholar is included among the top collaborators of Zhao Lv 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 Zhao Lv. Zhao Lv 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.
Hu, Shiang, et al.. (2025). How do the resting EEG preprocessing states affect the outcomes of postprocessing?. NeuroImage. 310. 121122–121122. 1 indexed citations
2.
Lv, Zhao, et al.. (2025). STMTNet: Spatio-Temporal Multiscale Triad Network for Cropland Change Detection in Remote Sensing Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 26005–26020.
3.
Fan, Cunhang, et al.. (2024). Multi-Level Contrastive Learning: Hierarchical Alleviation of Heterogeneity in Multimodal Sentiment Analysis. IEEE Transactions on Affective Computing. 16(1). 207–222. 18 indexed citations
4.
Fan, Cunhang, et al.. (2024). MSFNet: Multi-Scale Fusion Network for Brain-Controlled Speaker Extraction. 1652–1661. 7 indexed citations
5.
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
6.
Fan, Cunhang, Zhao Lv, Shan Liang, et al.. (2023). VLP2MSA: Expanding vision-language pre-training to multimodal sentiment analysis. Knowledge-Based Systems. 283. 111136–111136. 11 indexed citations
7.
Fan, Cunhang, et al.. (2023). Subband fusion of complex spectrogram for fake speech detection. Speech Communication. 155. 102988–102988. 5 indexed citations
8.
Fan, Cunhang, et al.. (2023). ICaps-ResLSTM: Improved capsule network and residual LSTM for EEG emotion recognition. Biomedical Signal Processing and Control. 87. 105422–105422. 42 indexed citations
9.
Zhang, Xu, et al.. (2023). Similarity Function for One-Shot Learning to Enhance the Flexibility of Myoelectric Interfaces. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 1697–1706. 6 indexed citations
10.
Fan, Cunhang, et al.. (2023). An Investigation of Olfactory-Enhanced Video on EEG-Based Emotion Recognition. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 1602–1613. 37 indexed citations
11.
Hu, Sai, Da Xiao, Zhenyu Zhang, et al.. (2023). Microstate fusion across frequency bands alleviates the use of deep learning models for EEG emotion recognition. International Journal of Psychophysiology. 188. 86–86.
12.
13.
Cao, Shuai, et al.. (2022). DATA AUGMENTATION FOR FMRI-BASED FUNCTIONAL CONNECTIVITY AND ITS APPLICATION TO CROSS-SITE ADHD CLASSIFICATION. IEEE Transactions on Instrumentation and Measurement. 1–1. 31 indexed citations
14.
Hu, Shiang, et al.. (2022). OVPD: Odor-Video Elicited Physiological Signal Database for Emotion Recognition. IEEE Transactions on Instrumentation and Measurement. 71. 1–12. 17 indexed citations
15.
Wu, Xiaopei, et al.. (2019). How many channels are suitable for independent component analysis in motor imagery brain-computer interface. Biomedical Signal Processing and Control. 50. 103–120. 14 indexed citations
16.
Wu, Xiaopei, et al.. (2019). To Explore the Potentials of Independent Component Analysis in Brain-Computer Interface of Motor Imagery. IEEE Journal of Biomedical and Health Informatics. 24(3). 775–787. 32 indexed citations
17.
Zhang, Chao, et al.. (2018). Robust EOG-based saccade recognition using multi-channel blind source deconvolution. Biomedizinische Technik/Biomedical Engineering. 64(3). 309–324. 3 indexed citations
18.
Lv, Zhao, et al.. (2017). Design and Implementation of a Reading Auxiliary Apparatus Based on Electrooculography. IEEE Access. 5. 3841–3847. 10 indexed citations
19.
Lv, Zhao, et al.. (2017). A Robust Online Saccadic Eye Movement Recognition Method Combining Electrooculography and Video. IEEE Access. 5. 17997–18003. 6 indexed citations
20.
Wu, Xiaopei, et al.. (2016). A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface. PLoS ONE. 11(9). e0162657–e0162657. 41 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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