Xiaolin Fang

634 total citations
28 papers, 371 citations indexed

About

Xiaolin Fang is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Xiaolin Fang has authored 28 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Networks and Communications, 10 papers in Computer Vision and Pattern Recognition and 6 papers in Artificial Intelligence. Recurrent topics in Xiaolin Fang's work include Energy Efficient Wireless Sensor Networks (8 papers), Mobile Ad Hoc Networks (6 papers) and IoT and Edge/Fog Computing (5 papers). Xiaolin Fang is often cited by papers focused on Energy Efficient Wireless Sensor Networks (8 papers), Mobile Ad Hoc Networks (6 papers) and IoT and Edge/Fog Computing (5 papers). Xiaolin Fang collaborates with scholars based in China, United States and Sweden. Xiaolin Fang's co-authors include Jianzhong Li, Zhipeng Cai, Siyao Cheng, Cewu Lu, Jianwen Xie, Hong Gao, Guansong Lu, Hao-Shu Fang, Yu‐Wing Tai and Yingshu Li and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Industrial Informatics and Neurocomputing.

In The Last Decade

Xiaolin Fang

27 papers receiving 368 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaolin Fang China 11 160 155 87 82 30 28 371
Jiashen Cao United States 9 163 1.0× 173 1.1× 127 1.5× 94 1.1× 36 1.2× 18 357
Vicent Sanz Marco United Kingdom 8 143 0.9× 109 0.7× 94 1.1× 61 0.7× 50 1.7× 14 297
Chuntao Ding China 10 151 0.9× 118 0.8× 72 0.8× 31 0.4× 55 1.8× 29 310
Zhonghao Lyu China 9 150 0.9× 63 0.4× 82 0.9× 207 2.5× 17 0.6× 21 493
Shuochao Yao United States 11 90 0.6× 155 1.0× 110 1.3× 64 0.8× 15 0.5× 19 312
Wenqi Zhou China 6 176 1.1× 50 0.3× 76 0.9× 145 1.8× 48 1.6× 7 306
Lunyuan Chen China 10 217 1.4× 58 0.4× 117 1.3× 234 2.9× 57 1.9× 11 421
Aveek Dutta United States 13 227 1.4× 42 0.3× 66 0.8× 209 2.5× 36 1.2× 48 414
Jinfeng Lai China 7 103 0.6× 156 1.0× 171 2.0× 121 1.5× 106 3.5× 12 362
Nadine Abbas Lebanon 10 231 1.4× 37 0.2× 66 0.8× 147 1.8× 30 1.0× 30 333

Countries citing papers authored by Xiaolin Fang

Since Specialization
Citations

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

Fields of papers citing papers by Xiaolin Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaolin Fang

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaolin Fang. A scholar is included among the top collaborators of Xiaolin Fang 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 Xiaolin Fang. Xiaolin Fang 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.
Xue, Yingying, et al.. (2024). Relation-oriented few-shot knowledge graph prototype networks. Neurocomputing. 575. 127242–127242. 2 indexed citations
2.
Fang, Xiaolin, et al.. (2024). SDRNet: Camouflaged object detection with independent reconstruction of structure and detail. Knowledge-Based Systems. 299. 112051–112051. 18 indexed citations
3.
Qian, Weiqi, et al.. (2024). Promoting camouflaged object detection through novel edge–target interaction and frequency-spatial fusion. Neurocomputing. 617. 129064–129064. 1 indexed citations
4.
Fang, Xiaolin, Caelan Reed Garrett, Clemens Eppner, et al.. (2024). DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability. 1412–1419. 5 indexed citations
5.
Zhu, Tongxin, Zhipeng Cai, Xiaolin Fang, Junzhou Luo, & Ming Yang. (2022). Correlation Aware Scheduling for Edge-Enabled Industrial Internet of Things. IEEE Transactions on Industrial Informatics. 18(11). 7967–7976. 3 indexed citations
6.
Xue, Yingying, Aibo Song, Xiaolin Fang, et al.. (2022). Intra- and inter-semantic with multi-scale evolving patterns for dynamic graph learning. Knowledge-Based Systems. 260. 110167–110167. 2 indexed citations
7.
Bi, Ran, Ting Peng, Jiankang Ren, Xiaolin Fang, & Guozhen Tan. (2022). Joint Service Placement and Computation Scheduling in Edge Clouds. 47–56. 7 indexed citations
8.
Xie, Jianwen, Zilong Zheng, Xiaolin Fang, Song‐Chun Zhu, & Ying Wu. (2021). Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(8). 1–1. 5 indexed citations
9.
Fang, Xiaolin, Zhipeng Cai, Wenyi Tang, et al.. (2020). Job Scheduling to Minimize Total Completion Time on Multiple Edge Servers. IEEE Transactions on Network Science and Engineering. 7(4). 2245–2255. 17 indexed citations
10.
Xie, Jianwen, Zilong Zheng, Xiaolin Fang, Song‐Chun Zhu, & Ying Wu. (2019). Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Multi-Modal Conditional Learning. arXiv (Cornell University). 3 indexed citations
11.
Fang, Xiaolin, Junzhou Luo, Guangchun Luo, et al.. (2018). Big Data Transmission in Industrial IoT Systems With Small Capacitor Supplying Energy. IEEE Transactions on Industrial Informatics. 15(4). 2360–2371. 14 indexed citations
12.
Fang, Hao-Shu, Guansong Lu, Xiaolin Fang, et al.. (2018). Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer. 70–78. 83 indexed citations
13.
Pan, Bowen, et al.. (2018). Recurrent Residual Module for Fast Inference in Videos. 1536–1545. 24 indexed citations
14.
Chen, Quan, Hong Gao, Siyao Cheng, et al.. (2017). Centralized and Distributed Delay-Bounded Scheduling Algorithms for Multicast in Duty-Cycled Wireless Sensor Networks. IEEE/ACM Transactions on Networking. 25(6). 3573–3586. 21 indexed citations
15.
Yang, Ming, Junzhou Luo, Wenjia Wu, & Xiaolin Fang. (2016). Energy-efficient activation of nodes and radios in multi-radio WLAN mesh networks. International Journal of Sensor Networks. 1(1). 1–1. 1 indexed citations
16.
Fang, Xiaolin, et al.. (2015). Detecting deterioration of nearsightness. 408–409.
17.
Gao, Hong, Xiaolin Fang, Jianzhong Li, & Yingshu Li. (2014). Data Collection in Multi-Application Sharing Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems. 26(2). 403–412. 17 indexed citations
18.
Fang, Xiaolin, Hong Gao, & Jianzhong Li. (2013). Reliability-Aware Power Adjustment in Air-Soil Wireless Sensor Networks. Ad Hoc & Sensor Wireless Networks. 18. 203–223. 1 indexed citations
19.
Li, Jianzhong, et al.. (2009). Enabling epsilon-Approximate Querying in Sensor Networks.. Very Large Data Bases. 2. 169–180. 4 indexed citations
20.
Liu, Yü, Jianzhong Li, Hong Gao, & Xiaolin Fang. (2009). Enabling ε-approximate querying in sensor networks. Proceedings of the VLDB Endowment. 2(1). 169–180. 6 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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