Lida Li

1.4k total citations · 1 hit paper
18 papers, 940 citations indexed

About

Lida Li is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Signal Processing. According to data from OpenAlex, Lida Li has authored 18 papers receiving a total of 940 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 5 papers in Electrical and Electronic Engineering and 3 papers in Signal Processing. Recurrent topics in Lida Li's work include Advanced Fiber Optic Sensors (5 papers), Image Enhancement Techniques (4 papers) and Biometric Identification and Security (3 papers). Lida Li is often cited by papers focused on Advanced Fiber Optic Sensors (5 papers), Image Enhancement Techniques (4 papers) and Biometric Identification and Security (3 papers). Lida Li collaborates with scholars based in China, Hong Kong and Cayman Islands. Lida Li's co-authors include Lingxiao Yang, Xiaohua Xie, Ru‐Yuan Zhang, Lei Zhang, Zisheng Cao, Hui Zeng, Lin Zhang, Meng Yang, Ying Shen and Anqi Yang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Applied Surface Science.

In The Last Decade

Lida Li

14 papers receiving 925 citations

Hit Papers

SimAM: A Simple, Parameter-Free Attention Module for Conv... 2021 2026 2022 2024 2021 100 200 300 400
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. SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks
    2021 499 citations Lingxiao Yang, Ru‐Yuan Zhang et al. International Conference on Machine Learning profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lida Li China 7 619 185 116 101 78 18 940
Mamoona Naveed Asghar Ireland 17 723 1.2× 152 0.8× 80 0.7× 48 0.5× 239 3.1× 64 1.2k
Yasar Abbas Ur Rehman Hong Kong 12 392 0.6× 166 0.9× 43 0.4× 34 0.3× 56 0.7× 24 590
Zhijie Huang China 8 453 0.7× 55 0.3× 82 0.7× 108 1.1× 106 1.4× 14 864
Haniza Yazid Malaysia 17 509 0.8× 56 0.3× 200 1.7× 117 1.2× 150 1.9× 72 1.1k
Lei Sun China 13 360 0.6× 138 0.7× 48 0.4× 38 0.4× 60 0.8× 65 675
Patrik Kamencay Slovakia 16 429 0.7× 56 0.3× 60 0.5× 42 0.4× 160 2.1× 92 780
Hai Min China 16 739 1.2× 128 0.7× 213 1.8× 20 0.2× 113 1.4× 31 951
Suprava Patnaik India 13 329 0.5× 154 0.8× 108 0.9× 16 0.2× 114 1.5× 73 645
A. Lynn Abbott United States 17 540 0.9× 99 0.5× 135 1.2× 15 0.1× 59 0.8× 85 1.0k
Ting Zhao China 12 535 0.9× 93 0.5× 106 0.9× 15 0.1× 91 1.2× 50 1.0k

Countries citing papers authored by Lida Li

Since Specialization
Citations

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

Fields of papers citing papers by Lida Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lida Li

This figure shows the co-authorship network connecting the top 25 collaborators of Lida Li. A scholar is included among the top collaborators of Lida Li 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 Lida Li. Lida Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Chen, Hailiang, et al.. (2025). High performance ethanol gas sensor based on fiber ring laser with a nematic liquid crystal film embedded Sagnac interferometer. Sensors and Actuators A Physical. 387. 116481–116481.
2.
3.
Gao, Zhigang, et al.. (2025). Label-Free In Situ Detection of DNA Hybridization Based on Long-Range Surface Plasmon Resonance in Microstructured Optical Fiber. IEEE Transactions on Instrumentation and Measurement. 74. 1–7.
4.
Li, Lida, Zisheng Cao, Minchen Wei, et al.. (2025). High-Resolution Photo Enhancement in Real-Time: A Laplacian Pyramid Network. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(3). 2170–2185.
5.
Li, Lida, Hailiang Chen, Xiaoya Fan, et al.. (2024). A Wide Range Curvature Sensor Based on Fiber Ring Laser With a Long-Period Fiber Grating. IEEE Transactions on Instrumentation and Measurement. 73. 1–10. 1 indexed citations
6.
Chen, Hailiang, Xiaoya Fan, Sa Zhang, et al.. (2024). Highly Sensitive Strain and Temperature Sensors Based on Vernier Effect in Cascaded Mach–Zehnder Interferometer and Sagnac Interferometer. IEEE Transactions on Instrumentation and Measurement. 73. 1–10. 6 indexed citations
7.
Li, Lida, et al.. (2024). Toward Blind Flare Removal Using Knowledge-Driven Flare-Level Estimator. IEEE Transactions on Image Processing. 33. 6114–6128. 1 indexed citations
8.
Li, Lida, Jiangtao Xie, Peihua Li, & Lei Zhang. (2021). Detachable Second-Order Pooling: Toward High-Performance First-Order Networks. IEEE Transactions on Neural Networks and Learning Systems. 33(8). 3400–3414. 2 indexed citations
9.
Yang, Lingxiao, Ru‐Yuan Zhang, Lida Li, & Xiaohua Xie. (2021). SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks. International Conference on Machine Learning. 11863–11874. 499 indexed citations breakdown →
10.
Li, Minghan, Shuai Li, Lida Li, & Lei Zhang. (2021). Spatial Feature Calibration and Temporal Fusion for Effective One-stage Video Instance Segmentation. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 11210–11219. 28 indexed citations
11.
Zeng, Hui, Jianrui Cai, Lida Li, Zisheng Cao, & Lei Zhang. (2020). Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(4). 1–1. 160 indexed citations
12.
Zeng, Hui, Lida Li, Zisheng Cao, & Lei Zhang. (2019). Reliable and Efficient Image Cropping: A Grid Anchor Based Approach. 5942–5950. 46 indexed citations
13.
Dai, Tao, et al.. (2018). Content-Aware Bilateral Filtering. 19. 1–6. 2 indexed citations
14.
Zhang, Lin, Lida Li, Anqi Yang, Ying Shen, & Meng Yang. (2017). Towards contactless palmprint recognition: A novel device, a new benchmark, and a collaborative representation based identification approach. Pattern Recognition. 69. 199–212. 172 indexed citations
15.
Zhang, Lin, Lida Li, Hongyu Li, & Meng Yang. (2016). 3D Ear Identification Using Block-Wise Statistics-Based Features and LC-KSVD. IEEE Transactions on Multimedia. 18(8). 1531–1541. 13 indexed citations
16.
Chen, Hai, Xiong Zhu, Hong Cai, et al.. (2015). [Discovery of Burkholderia Thailandensis isolated from melioidosis endemic areas of Hainan China].. PubMed. 36(1). 97–8. 3 indexed citations
17.
18.
Li, Lida, Lin Zhang, & Hongyu Li. (2015). 3D ear identification using LC-KSVD and local histograms of surface types. 1–6. 1 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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