Kaiyang Liao

400 total citations
35 papers, 277 citations indexed

About

Kaiyang Liao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Kaiyang Liao has authored 35 papers receiving a total of 277 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 7 papers in Media Technology. Recurrent topics in Kaiyang Liao's work include Advanced Image and Video Retrieval Techniques (12 papers), Image Retrieval and Classification Techniques (8 papers) and Domain Adaptation and Few-Shot Learning (7 papers). Kaiyang Liao is often cited by papers focused on Advanced Image and Video Retrieval Techniques (12 papers), Image Retrieval and Classification Techniques (8 papers) and Domain Adaptation and Few-Shot Learning (7 papers). Kaiyang Liao collaborates with scholars based in China and Singapore. Kaiyang Liao's co-authors include Guangfeng Lin, Guizhong Liu, Fan Zhao, Yajun Chen, Bangyong Sun, Xiaobing Kang, Congjun Cao, Ke Gu, Wei Wang and Lei Hao and has published in prestigious journals such as IEEE Access, Pattern Recognition and IEEE Internet of Things Journal.

In The Last Decade

Kaiyang Liao

27 papers receiving 271 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kaiyang Liao China	8	193	96	47	27	22	35	277
Bei Li China	10	137 0.7×	136 1.4×	18 0.4×	13 0.5×	11 0.5×	29	264
Chen Gao China	12	328 1.7×	139 1.4×	19 0.4×	19 0.7×	5 0.2×	19	410
Amit Gruber Israel	6	178 0.9×	179 1.9×	41 0.9×	27 1.0×	13 0.6×	6	347
Shide Du China	11	219 1.1×	231 2.4×	33 0.7×	18 0.7×	26 1.2×	28	345
Shuhan Qi China	10	145 0.8×	153 1.6×	17 0.4×	13 0.5×	5 0.2×	49	295
Carl Case United States	4	236 1.2×	50 0.5×	90 1.9×	17 0.6×	4 0.2×	8	290
Geonmo Gu South Korea	7	205 1.1×	160 1.7×	14 0.3×	11 0.4×	10 0.5×	10	259
Mahdi Jampour Iran	10	245 1.3×	78 0.8×	58 1.2×	3 0.1×	5 0.2×	35	326
Dong Yin China	8	78 0.4×	82 0.9×	25 0.5×	21 0.8×	3 0.1×	29	224
Juhua Hu United States	9	249 1.3×	246 2.6×	15 0.3×	8 0.3×	14 0.6×	27	390

Countries citing papers authored by Kaiyang Liao

Since Specialization

Citations

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

Fields of papers citing papers by Kaiyang Liao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaiyang Liao

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

All Works

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20 of 20 papers shown

Lin, Guangfeng, et al.. (2025). High-Order Structure-Preserving Graph Neural Network for Few-Shot Learning. IEEE Internet of Things Journal. 12(11). 17987–18003.

Liao, Kaiyang, et al.. (2025). Cross-sample feature interaction enhancement for few-shot fine-grained classification. Displays. 90. 103157–103157.

Liu, Haiwen, et al.. (2025). Detection of small defects on packaging prints under sample-few conditions. Signal Image and Video Processing. 19(4).

Lin, Guangfeng, Wenchao Wei, Xiaobing Kang, Kaiyang Liao, & Erhu Zhang. (2024). Deep graph layer information mining convolutional network. Pattern Recognition. 154. 110593–110593.

Huang, Gang, et al.. (2023). 互补注意多样性特征融合网络的细粒度分类. Journal of Image and Graphics. 28(8). 2420–2431. 1 indexed citations

Li, Yumei, et al.. (2023). Layer similarity guiding few-shot Chinese style transfer. The Visual Computer. 40(4). 2265–2278. 4 indexed citations

Liao, Kaiyang, et al.. (2023). Approximate object location deep visual representations for image retrieval. Displays. 77. 102376–102376. 10 indexed citations

Liao, Kaiyang, et al.. (2023). Feature channel interaction long-tailed image classification model based on dual attention. Signal Image and Video Processing. 18(2). 1661–1670. 2 indexed citations

Chen, Wenqian, et al.. (2023). Small target detection algorithm for printing defects detection based on context structure perception and multi-scale feature fusion. Signal Image and Video Processing. 18(1). 657–667. 6 indexed citations

10.

Wei, Wenchao, et al.. (2022). Survey of graph network hierarchical information mining for classification. Journal of Image and Graphics. 27(10). 2916–2936. 2 indexed citations

11.

Liao, Kaiyang, et al.. (2022). Image Retrieval Based on the Weighted and Regional Integration of CNN Features. KSII Transactions on Internet and Information Systems. 16(3). 1 indexed citations

12.

Liao, Kaiyang, et al.. (2022). Coordinate feature fusion networks for fine-grained image classification. Signal Image and Video Processing. 17(3). 807–815. 1 indexed citations

13.

Liao, Kaiyang, et al.. (2022). No-reference image quality assessment of multi-level residual feature augmentation. Signal Image and Video Processing. 17(4). 1275–1283.

14.

Liao, Kaiyang, et al.. (2021). A deep multi-feature distance metric learning method for pedestrian re-identification. Multimedia Tools and Applications. 80(15). 23113–23131. 6 indexed citations

15.

Lin, Guangfeng, Xiaobing Kang, Kaiyang Liao, Fan Zhao, & Yajun Chen. (2021). Deep graph learning for semi-supervised classification. Pattern Recognition. 118. 108039–108039. 34 indexed citations

16.

Lin, Guangfeng, Jing Wang, Kaiyang Liao, Fan Zhao, & Wanjun Chen. (2020). Structure Fusion Based on Graph Convolutional Networks for Node Classification in Citation Networks. Electronics. 9(3). 432–432. 9 indexed citations

17.

Lin, Guangfeng, et al.. (2019). Transfer Feature Generating Networks With Semantic Classes Structure for Zero-Shot Learning. IEEE Access. 7. 176470–176483. 6 indexed citations

18.

Liao, Kaiyang, et al.. (2019). Image quality assessment via spatial‐transformed domains multi‐feature fusion. IET Image Processing. 14(4). 648–657. 6 indexed citations

19.

Gu, Ke, et al.. (2018). Full-Reference Image Quality Assessment by Combining Features in Spatial and Frequency Domains. IEEE Transactions on Broadcasting. 65(1). 138–151. 34 indexed citations

20.

Liao, Kaiyang. (2009). Least square method based repairing method for broken seal imprint contour. Jisuanji gongcheng yu sheji.

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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