Qianfen Jiao

648 total citations · 1 hit paper
12 papers, 438 citations indexed

About

Qianfen Jiao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Qianfen Jiao has authored 12 papers receiving a total of 438 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 1 paper in Signal Processing. Recurrent topics in Qianfen Jiao's work include Domain Adaptation and Few-Shot Learning (7 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Advanced Image Processing Techniques (4 papers). Qianfen Jiao is often cited by papers focused on Domain Adaptation and Few-Shot Learning (7 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Advanced Image Processing Techniques (4 papers). Qianfen Jiao collaborates with scholars based in China and Hong Kong. Qianfen Jiao's co-authors include Hau−San Wong, Wenming Cao, Rui Li, Si Wu, Si Wu, Cheng Liu, Zhiwen Yu, Zhongfan Zhang, Wenhao Wu and Zhi‐Ri Tang and has published in prestigious journals such as Pattern Recognition, Information Sciences and Knowledge-Based Systems.

In The Last Decade

Qianfen Jiao

12 papers receiving 427 citations

Hit Papers

Model Adaptation: Unsupervised Domain Adaptation Without ... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qianfen Jiao China 6 312 298 53 33 18 12 438
Songlin Dong China 9 392 1.3× 232 0.8× 59 1.1× 22 0.7× 23 1.3× 19 482
Xinyuan Chang China 6 332 1.1× 247 0.8× 53 1.0× 20 0.6× 19 1.1× 8 430
Zhihe Lu China 8 263 0.8× 384 1.3× 37 0.7× 18 0.5× 28 1.6× 16 458
Pengfei Ge China 9 280 0.9× 240 0.8× 35 0.7× 34 1.0× 10 0.6× 10 387
Shuhao Cui China 5 380 1.2× 277 0.9× 53 1.0× 41 1.2× 29 1.6× 9 484
Aming Wu China 14 427 1.4× 526 1.8× 61 1.2× 14 0.4× 44 2.4× 32 694
Tong Che Algeria 7 199 0.6× 140 0.5× 42 0.8× 13 0.4× 10 0.6× 9 268
Pau Panareda Busto Germany 4 334 1.1× 290 1.0× 38 0.7× 43 1.3× 23 1.3× 5 444

Countries citing papers authored by Qianfen Jiao

Since Specialization
Citations

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

Fields of papers citing papers by Qianfen Jiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qianfen Jiao

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

All Works

12 of 12 papers shown
1.
Jiao, Qianfen, et al.. (2024). Cluster-based Adversarial Decision Boundary for domain-adaptive open set recognition. Knowledge-Based Systems. 289. 111478–111478. 1 indexed citations
2.
Jiao, Qianfen, et al.. (2024). DA-GAN: Dual-attention generative adversarial networks for real-world exquisite makeup transfer. Pattern Recognition. 158. 111049–111049. 2 indexed citations
3.
Wu, Si, et al.. (2022). TSEV-GAN: Generative Adversarial Networks with Target-aware Style Encoding and Verification for facial makeup transfer. Knowledge-Based Systems. 257. 109958–109958. 16 indexed citations
4.
Wu, Wenhao, et al.. (2022). Learning scene-adaptive pseudo annotations for pedestrian detection in semi-supervised scenarios. Knowledge-Based Systems. 243. 108439–108439. 2 indexed citations
5.
Tang, Zhi‐Ri, et al.. (2022). Source-Free Unsupervised Cross-Domain Pedestrian Detection via Pseudo Label Mining and Screening. 2022 IEEE International Conference on Multimedia and Expo (ICME). 1–6. 2 indexed citations
6.
Jiao, Qianfen, et al.. (2022). Perturbation-insensitive cross-domain image enhancement for low-quality face verification. Information Sciences. 608. 1183–1201. 6 indexed citations
7.
Cao, Wenming, Zhongfan Zhang, Cheng Liu, et al.. (2022). Unsupervised discriminative feature learning via finding a clustering-friendly embedding space. Pattern Recognition. 129. 108768–108768. 27 indexed citations
8.
Jiao, Qianfen, et al.. (2021). High Fidelity GAN Inversion via Prior Multi-Subspace Feature Composition. Proceedings of the AAAI Conference on Artificial Intelligence. 35(9). 8366–8374. 1 indexed citations
9.
Jiao, Qianfen, et al.. (2021). DDAT: Dual domain adaptive translation for low-resolution face verification in the wild. Pattern Recognition. 120. 108107–108107. 10 indexed citations
11.
Li, Rui, Qianfen Jiao, Wenming Cao, Hau−San Wong, & Si Wu. (2020). Model Adaptation: Unsupervised Domain Adaptation Without Source Data. ArXiv.org. 9638–9647. 326 indexed citations breakdown →
12.
Li, Rui, Wenming Cao, Qianfen Jiao, Si Wu, & Hau−San Wong. (2020). Simplified unsupervised image translation for semantic segmentation adaptation. Pattern Recognition. 105. 107343–107343. 42 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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