Runlong Xia

2.2k total citations · 5 hit papers
24 papers, 1.5k citations indexed

About

Runlong Xia is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Runlong Xia has authored 24 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 12 papers in Media Technology and 2 papers in Artificial Intelligence. Recurrent topics in Runlong Xia's work include Advanced Image Processing Techniques (16 papers), Generative Adversarial Networks and Image Synthesis (11 papers) and Advanced Vision and Imaging (9 papers). Runlong Xia is often cited by papers focused on Advanced Image Processing Techniques (16 papers), Generative Adversarial Networks and Image Synthesis (11 papers) and Advanced Vision and Imaging (9 papers). Runlong Xia collaborates with scholars based in China. Runlong Xia's co-authors include Yuantao Chen, Kai Yang, Ke Zou, Jingbo Xie, Qian Zhang, Jiajun Tao, Jie Xiong, Xi Chen, Binbin Ren and Ke Gu and has published in prestigious journals such as Expert Systems with Applications, Applied Soft Computing and Computer Vision and Image Understanding.

In The Last Decade

Runlong Xia

23 papers receiving 1.5k citations

Hit Papers

Image super-resolution reconstruction based on feature ma... 2021 2026 2022 2024 2021 2024 2023 2024 2025 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Runlong Xia China 19 1.1k 401 222 82 78 24 1.5k
Vishwanath A. Sindagi United States 11 1.6k 1.4× 429 1.1× 434 2.0× 107 1.3× 73 0.9× 15 2.0k
Xu Wang China 25 1.6k 1.4× 349 0.9× 394 1.8× 68 0.8× 76 1.0× 136 2.3k
Renjie Liao Canada 20 1.6k 1.4× 451 1.1× 461 2.1× 51 0.6× 64 0.8× 46 2.2k
Yong Zhao China 17 1.0k 0.9× 352 0.9× 256 1.2× 70 0.9× 114 1.5× 153 1.4k
Chenglizhao Chen China 28 1.8k 1.6× 398 1.0× 287 1.3× 74 0.9× 61 0.8× 92 2.1k
Zhiyong Gao China 21 1.8k 1.6× 272 0.7× 150 0.7× 116 1.4× 98 1.3× 97 2.2k
Li Song China 25 1.5k 1.3× 190 0.5× 261 1.2× 53 0.6× 95 1.2× 242 2.1k
Zhaoqing Pan China 25 1.5k 1.3× 195 0.5× 310 1.4× 47 0.6× 57 0.7× 70 2.1k

Countries citing papers authored by Runlong Xia

Since Specialization
Citations

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

Fields of papers citing papers by Runlong Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Runlong Xia

This figure shows the co-authorship network connecting the top 25 collaborators of Runlong Xia. A scholar is included among the top collaborators of Runlong Xia 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 Runlong Xia. Runlong Xia 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.
Chen, Yuantao, et al.. (2025). CAAT: Image super-resolution algorithm via channel attention and transformer. Array. 28. 100628–100628.
2.
Chen, Yuantao, Runlong Xia, Kai Yang, & Ke Zou. (2025). Dual degradation image inpainting method via adaptive feature fusion and U-net network. Applied Soft Computing. 174. 113010–113010. 15 indexed citations breakdown →
3.
Chen, Yuantao, Runlong Xia, Kai Yang, & Ke Zou. (2024). Image inpainting algorithm based on inference attention module and two-stage network. Engineering Applications of Artificial Intelligence. 137. 109181–109181. 45 indexed citations
4.
Chen, Yuantao, Runlong Xia, Kai Yang, & Ke Zou. (2024). DNNAM: Image inpainting algorithm via deep neural networks and attention mechanism. Applied Soft Computing. 154. 111392–111392. 100 indexed citations breakdown →
5.
Chen, Yuantao, Runlong Xia, Kai Yang, & Ke Zou. (2024). MICU: Image super-resolution via multi-level information compensation and U-net. Expert Systems with Applications. 245. 123111–123111. 108 indexed citations breakdown →
6.
Chen, Yuantao, Runlong Xia, Kai Yang, & Ke Zou. (2023). MFMAM: Image inpainting via multi-scale feature module with attention module. Computer Vision and Image Understanding. 238. 103883–103883. 80 indexed citations
7.
Chen, Yuantao, Runlong Xia, Ke Zou, & Kai Yang. (2023). RNON: image inpainting via repair network and optimization network. International Journal of Machine Learning and Cybernetics. 14(9). 2945–2961. 54 indexed citations
8.
Chen, Yuantao, Runlong Xia, Ke Zou, & Kai Yang. (2023). FFTI: Image inpainting algorithm via features fusion and two-steps inpainting. Journal of Visual Communication and Image Representation. 91. 103776–103776. 88 indexed citations
9.
Chen, Yuantao, Runlong Xia, Kai Yang, & Ke Zou. (2023). GCAM: lightweight image inpainting via group convolution and attention mechanism. International Journal of Machine Learning and Cybernetics. 15(5). 1815–1825. 32 indexed citations
10.
Chen, Yuantao, Runlong Xia, Kai Yang, & Ke Zou. (2023). MFFN: image super-resolution via multi-level features fusion network. The Visual Computer. 40(2). 489–504. 102 indexed citations breakdown →
11.
Xia, Runlong, et al.. (2023). Using random forest to disentangle the effects of environmental conditions on height-to-diameter ratio of Engelmann spruce. New Forests. 55(2). 213–229. 2 indexed citations
12.
Chen, Yuantao, Runlong Xia, Kai Yang, & Ke Zou. (2023). DGCA: high resolution image inpainting via DR-GAN and contextual attention. Multimedia Tools and Applications. 82(30). 47751–47771. 43 indexed citations
13.
Xia, Runlong, Yuantao Chen, & Binbin Ren. (2022). Improved anti-occlusion object tracking algorithm using Unscented Rauch-Tung-Striebel smoother and kernel correlation filter. Journal of King Saud University - Computer and Information Sciences. 34(8). 6008–6018. 82 indexed citations
14.
Chen, Yuantao, et al.. (2021). An improved local binary pattern method for pollen image classification and recognition. Computers & Electrical Engineering. 90. 106983–106983. 14 indexed citations
15.
Chen, Yuantao, Haopeng Zhang, Jiajun Tao, et al.. (2021). Research on image inpainting algorithm of improved total variation minimization method. Journal of Ambient Intelligence and Humanized Computing. 14(5). 5555–5564. 78 indexed citations
16.
Chen, Yuantao, Ke Gu, Runlong Xia, et al.. (2021). Image super-resolution reconstruction based on feature map attention mechanism. Applied Intelligence. 51(7). 4367–4380. 186 indexed citations breakdown →
17.
Xia, Runlong, et al.. (2021). Research on object tracking algorithm via adaptive multi-feature fusion. 82–82. 1 indexed citations
18.
Chen, Yuantao, Jiajun Tao, Jie Xiong, et al.. (2020). Research of improving semantic image segmentation based on a feature fusion model. Journal of Ambient Intelligence and Humanized Computing. 13(11). 5033–5045. 89 indexed citations
19.
Chen, Yuantao, Haopeng Zhang, Xi Chen, et al.. (2020). Research on image Inpainting algorithm of improved GAN based on two-discriminations networks. Applied Intelligence. 51(6). 3460–3474. 59 indexed citations
20.
Chen, Yuantao, Jiajun Tao, Qian Zhang, et al.. (2020). Saliency Detection via the Improved Hierarchical Principal Component Analysis Method. Wireless Communications and Mobile Computing. 2020. 1–12. 55 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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