Qi She

2.7k total citations · 2 hit papers
33 papers, 1.3k citations indexed

About

Qi She is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Qi She has authored 33 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 17 papers in Artificial Intelligence and 9 papers in Cognitive Neuroscience. Recurrent topics in Qi She's work include Advanced Neural Network Applications (9 papers), Neural dynamics and brain function (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Qi She is often cited by papers focused on Advanced Neural Network Applications (9 papers), Neural dynamics and brain function (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Qi She collaborates with scholars based in Hong Kong, China and Ireland. Qi She's co-authors include Zhengwei Wang, Tomás Ward, Aljoša Smolić, Changhu Wang, Eoin Brophy, Duo Li, Jie Hu, Qifeng Chen, Lei Zhu and Xiangtai Li and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Transactions on Signal Processing.

In The Last Decade

Qi She

31 papers receiving 1.3k citations

Hit Papers

align trajectories

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.

Involution: Inverting the Inherence of Convolution for Visual Recognition

2021 264 citations Duo Li, Jie Hu et al. Rare & Special e-Zone (The Hong Kong University of Science and Technology) profile →
Generative Adversarial Networks in Time Series: A Systematic Literature Review

2022 178 citations Eoin Brophy, Zhengwei Wang et al. ACM Computing Surveys profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qi She Hong Kong	15	779	458	148	118	116	33	1.3k
Hao Zhou China	19	617 0.8×	229 0.5×	134 0.9×	73 0.6×	90 0.8×	74	1.2k
Wee Kheng Leow Singapore	20	732 0.9×	464 1.0×	75 0.5×	82 0.7×	112 1.0×	80	1.4k
Quanfu Fan United States	18	1.3k 1.7×	587 1.3×	132 0.9×	251 2.1×	154 1.3×	48	2.1k
Hao Gao China	18	613 0.8×	503 1.1×	108 0.7×	153 1.3×	111 1.0×	116	1.4k
Xiaorui Zhang China	16	497 0.6×	346 0.8×	114 0.8×	111 0.9×	63 0.5×	82	1.2k
Zihang Jiang China	11	1.2k 1.6×	570 1.2×	132 0.9×	263 2.2×	93 0.8×	23	1.9k
Ali Thabet Saudi Arabia	13	709 0.9×	643 1.4×	79 0.5×	52 0.4×	77 0.7×	26	1.6k
Min Sun United States	21	1.6k 2.0×	565 1.2×	326 2.2×	129 1.1×	73 0.6×	86	2.0k
Hongkai Yu United States	22	1.3k 1.7×	438 1.0×	196 1.3×	249 2.1×	65 0.6×	85	1.9k
Yehui Tang China	15	862 1.1×	491 1.1×	101 0.7×	199 1.7×	69 0.6×	19	1.4k

Countries citing papers authored by Qi She

Since Specialization

Citations

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

Fields of papers citing papers by Qi She

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qi She

This figure shows the co-authorship network connecting the top 25 collaborators of Qi She. A scholar is included among the top collaborators of Qi She 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 Qi She. Qi She 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:

20 of 20 papers shown

Zhu, Lei, et al.. (2024). Boosting Weakly Supervised Object Localization and Segmentation With Domain Adaption. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(12). 8680–8695. 2 indexed citations

Shen, Zhengyang, Yibo Yang, Qi She, et al.. (2023). Newton design: designing CNNs with the family of Newton’s methods. Science China Information Sciences. 66(6). 3 indexed citations

Lomonaco, Vincenzo, Lorenzo Pellegrini, Pau Rodríguez, et al.. (2022). CVPR 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions. CINECA IRIS Institutial research information system (University of Pisa). 23 indexed citations

Brophy, Eoin, Zhengwei Wang, Qi She, & Tomás Ward. (2022). Generative Adversarial Networks in Time Series: A Systematic Literature Review. ACM Computing Surveys. 55(10). 1–31. 178 indexed citations breakdown →

Liu, Qi, Qi She, Vincenzo Lomonaco, et al.. (2022). Towards lifelong object recognition: A dataset and benchmark. Pattern Recognition. 130. 108819–108819. 4 indexed citations

Jing, Longlong, Lin Zhang, Ju He, et al.. (2022). Learning from Temporal Gradient for Semi-supervised Action Recognition. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 3242–3252. 54 indexed citations

Hou, Lu, et al.. (2022). Power Law in Deep Neural Networks: Sparse Network Generation and Continual Learning With Preferential Attachment. IEEE Transactions on Neural Networks and Learning Systems. 35(7). 8999–9013. 6 indexed citations

Li, Duo, Jie Hu, Changhu Wang, et al.. (2021). Involution: Inverting the Inherence of Convolution for Visual Recognition. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 12316–12325. 264 indexed citations breakdown →

Wang, Zhengwei, Qi She, & Tomás Ward. (2021). Generative Adversarial Networks in Computer Vision. ACM Computing Surveys. 54(2). 1–38. 144 indexed citations

10.

Wang, Zhengwei, Qi She, & Aljoša Smolić. (2021). ACTION-Net: Multipath Excitation for Action Recognition. 13209–13218. 163 indexed citations

11.

She, Qi, et al.. (2021). An Efficient and Flexible Spike Train Model Via Empirical Bayes. IEEE Transactions on Signal Processing. 69. 3236–3251.

12.

Wang, Zhengwei, Qi She, Alan F. Smeaton, Tomás Ward, & Graham Healy. (2020). Synthetic-Neuroscore: Using a neuro-AI interface for evaluating generative adversarial networks. Neurocomputing. 405. 26–36. 5 indexed citations

13.

Shi, Xuesong, Dongjiang Li, Pengpeng Zhao, et al.. (2020). Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAM. 3139–3145. 103 indexed citations

14.

She, Qi & Anqi Wu. (2019). Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks. arXiv (Cornell University). 454–464. 4 indexed citations

15.

Wang, Zhengwei, Qi She, & Tomás Ward. (2019). Generative Adversarial Networks: A Survey and Taxonomy.. arXiv (Cornell University). 33 indexed citations

16.

Wang, Zhengwei, Qi She, Alan F. Smeaton, Tomás Ward, & Graham Healy. (2019). Neuroscore: A Brain-inspired Evaluation Metric for Generative Adversarial Networks. arXiv (Cornell University). 5 indexed citations

17.

She, Qi, et al.. (2018). Weighted Network Density Predicts Range of Latent Variable Model Accuracy. PubMed. 2018. 2414–2417. 3 indexed citations

18.

Jelfs, Beth, et al.. (2016). Cross-frequency information transfer from EEG to EMG in grasping. PubMed. 2016. 4531–4534. 11 indexed citations

19.

She, Qi, Guanrong Chen, & Rosa H. M. Chan. (2016). Evaluating the Small-World-Ness of a Sampled Network: Functional Connectivity of Entorhinal-Hippocampal Circuitry. Scientific Reports. 6(1). 21468–21468. 24 indexed citations

20.

She, Qi. (2006). NEW METHOD FOR THE CALCULATION OF THE CHARACTERISTICS OF AERODYNAMIC BEARINGS. Jixie qiangdu. 3 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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