Linlin Liu

889 total citations
22 papers, 607 citations indexed

About

Linlin Liu is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Cognitive Neuroscience. According to data from OpenAlex, Linlin Liu has authored 22 papers receiving a total of 607 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 7 papers in Computational Mechanics and 3 papers in Cognitive Neuroscience. Recurrent topics in Linlin Liu's work include Generative Adversarial Networks and Image Synthesis (13 papers), 3D Shape Modeling and Analysis (7 papers) and Face recognition and analysis (6 papers). Linlin Liu is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (13 papers), 3D Shape Modeling and Analysis (7 papers) and Face recognition and analysis (6 papers). Linlin Liu collaborates with scholars based in China, Hong Kong and Singapore. Linlin Liu's co-authors include Haijun Zhang, Yuzhu Ji, Xiaofei Xu, Zhao Zhang, Shuicheng Yan, Q. M. Jonathan Wu, Dongliang Zhou, Zhenyuan Guo, Jun Wang and Wenyin Liu and has published in prestigious journals such as Chemical Communications, Scientific Reports and IEEE Access.

In The Last Decade

Linlin Liu

22 papers receiving 586 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Linlin Liu China 12 329 109 86 71 66 22 607
Shuhui Jiang China 13 261 0.8× 168 1.5× 47 0.5× 44 0.6× 37 0.6× 29 639
Youngmin Kim South Korea 10 271 0.8× 71 0.7× 67 0.8× 24 0.3× 50 0.8× 46 446
Yijun Li United States 16 1.2k 3.7× 190 1.7× 61 0.7× 32 0.5× 203 3.1× 42 1.4k
Antonios Symvonis Greece 11 184 0.6× 43 0.4× 51 0.6× 95 1.3× 166 2.5× 58 431
Michihiko Minoh Japan 13 473 1.4× 130 1.2× 30 0.3× 29 0.4× 32 0.5× 142 794
Shintami Chusnul Hidayati Indonesia 13 374 1.1× 255 2.3× 96 1.1× 9 0.1× 24 0.4× 71 952
Jingwen Ye China 12 606 1.8× 259 2.4× 36 0.4× 10 0.1× 107 1.6× 19 856
Laxmi Gewali United States 11 181 0.6× 133 1.2× 15 0.2× 88 1.2× 85 1.3× 52 482
Kang Zhang China 15 454 1.4× 81 0.7× 23 0.3× 55 0.8× 16 0.2× 66 711
Dino Schweitzer United States 12 177 0.5× 71 0.7× 105 1.2× 38 0.5× 125 1.9× 45 639

Countries citing papers authored by Linlin Liu

Since Specialization
Citations

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

Fields of papers citing papers by Linlin Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linlin Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Linlin Liu. A scholar is included among the top collaborators of Linlin Liu 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 Linlin Liu. Linlin Liu 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, Jingsong, et al.. (2025). Assessing the content and quality of GI bleeding information on Bilibili, TikTok, and YouTube: a cross-sectional study. Scientific Reports. 15(1). 14856–14856. 5 indexed citations
2.
Liu, Linlin, et al.. (2023). Collocated Clothing Synthesis with GANs Aided by Textual Information: A Multi-Modal Framework. ACM Transactions on Multimedia Computing Communications and Applications. 20(1). 1–25. 5 indexed citations
3.
Liu, Linlin, et al.. (2023). Toward Fashion Intelligence in the Big Data Era: State-of-the-Art and Future Prospects. IEEE Transactions on Consumer Electronics. 70(1). 36–57. 17 indexed citations
4.
Zhang, Haijun, Linlin Liu, Dongliang Zhou, et al.. (2022). Toward Intelligent Design: An AI-Based Fashion Designer Using Generative Adversarial Networks Aided by Sketch and Rendering Generators. IEEE Transactions on Multimedia. 25. 2323–2338. 52 indexed citations
5.
Wang, Tienan, et al.. (2022). When Does Competitive Learning Occur? The Impact of Alliance Network Embeddedness on Technological Invasion. British Journal of Management. 34(2). 1023–1041. 11 indexed citations
6.
Zhou, Dongliang, Haijun Zhang, Kai Yang, et al.. (2022). Learning to Synthesize Compatible Fashion Items Using Semantic Alignment and Collocation Classification: An Outfit Generation Framework. IEEE Transactions on Neural Networks and Learning Systems. 35(4). 5226–5240. 19 indexed citations
7.
Zhang, Haijun, et al.. (2021). TGAN: A simple model update strategy for visual tracking via template-guidance attention network. Neural Networks. 144. 61–74. 7 indexed citations
8.
Zhang, Xiaoli, et al.. (2021). An improved generative adversarial network for translating clothes from the human body to tiled image. Neural Computing and Applications. 33(14). 8445–8457. 3 indexed citations
9.
Liu, Linlin, Haijun Zhang, & Dongliang Zhou. (2021). Clothing generation by multi-modal embedding: A compatibility matrix-regularized GAN model. Image and Vision Computing. 107. 104097–104097. 9 indexed citations
10.
Liu, Linlin, Haijun Zhang, Yuzhu Ji, & Q. M. Jonathan Wu. (2019). Toward AI fashion design: An Attribute-GAN model for clothing match. Neurocomputing. 341. 156–167. 83 indexed citations
11.
Liu, Linlin, Haijun Zhang, Xiaofei Xu, Zhao Zhang, & Shuicheng Yan. (2019). Collocating Clothes With Generative Adversarial Networks Cosupervised by Categories and Attributes: A Multidiscriminator Framework. IEEE Transactions on Neural Networks and Learning Systems. 31(9). 3540–3554. 54 indexed citations
12.
Zhang, Haijun, et al.. (2019). Learning to Match Clothing From Textual Feature-Based Compatible Relationships. IEEE Transactions on Industrial Informatics. 16(11). 6750–6759. 18 indexed citations
13.
14.
Tseng, Kuo-Kun, Linlin Liu, Chao Wang, et al.. (2019). Robust Multistage ECG Identification for Astronaut Spacesuits With IoT Applications. IEEE Access. 7. 111662–111677. 4 indexed citations
15.
Yuan, Manman, Weiping Wang, Xiong Luo, Linlin Liu, & Wenbing Zhao. (2018). Finite-time anti-synchronization of memristive stochastic BAM neural networks with probabilistic time-varying delays. Chaos Solitons & Fractals. 113. 244–260. 28 indexed citations
16.
Zhang, Haijun, et al.. (2018). ClothingOut: a category-supervised GAN model for clothing segmentation and retrieval. Neural Computing and Applications. 32(9). 4519–4530. 66 indexed citations
17.
Guo, Zhenyuan, Linlin Liu, & Jun Wang. (2018). Multistability of Recurrent Neural Networks With Piecewise-Linear Radial Basis Functions and State-Dependent Switching Parameters. IEEE Transactions on Systems Man and Cybernetics Systems. 50(11). 4458–4471. 39 indexed citations
18.
Zhang, Haijun, et al.. (2018). Clothes Collocation Recommendations by Compatibility Learning. 179–186. 5 indexed citations
19.
Zhang, Haijun, et al.. (2018). Sitcom-star-based clothing retrieval for video advertising: a deep learning framework. Neural Computing and Applications. 31(11). 7361–7380. 78 indexed citations
20.
Gao, Fei, Linlin Liu, Na Ma, et al.. (2017). Synthesis of carbonylated heteroaromatic compounds via visible-light-driven intramolecular decarboxylative cyclization of o-alkynylated carboxylic acids. Chemical Communications. 53(61). 8533–8536. 26 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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