Weipeng Jing

1.7k total citations
121 papers, 1.1k citations indexed

About

Weipeng Jing is a scholar working on Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Weipeng Jing has authored 121 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Networks and Communications, 29 papers in Information Systems and 29 papers in Computer Vision and Pattern Recognition. Recurrent topics in Weipeng Jing's work include Remote-Sensing Image Classification (23 papers), Cloud Computing and Resource Management (22 papers) and Remote Sensing and LiDAR Applications (15 papers). Weipeng Jing is often cited by papers focused on Remote-Sensing Image Classification (23 papers), Cloud Computing and Resource Management (22 papers) and Remote Sensing and LiDAR Applications (15 papers). Weipeng Jing collaborates with scholars based in China, United States and Egypt. Weipeng Jing's co-authors include Guangsheng Chen, Houbing Song, Linhui Li, Donglin Di, Yue Han, Robertas Damaševičius, Mahmoud Emam, Marcin Woźniak, Jian Wang and Huihui Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and IEEE Access.

In The Last Decade

Weipeng Jing

110 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weipeng Jing China 20 274 257 256 233 230 121 1.1k
Lichuan Gu China 14 276 1.0× 392 1.5× 302 1.2× 212 0.9× 236 1.0× 55 1.5k
Zhiwei Ye China 20 234 0.9× 704 2.7× 492 1.9× 265 1.1× 186 0.8× 211 1.8k
Mansour Zuair Saudi Arabia 20 328 1.2× 404 1.6× 628 2.5× 301 1.3× 576 2.5× 50 1.8k
Yao‐Yi Chiang United States 22 104 0.4× 251 1.0× 441 1.7× 154 0.7× 198 0.9× 85 1.7k
Saleh Basalamah Saudi Arabia 18 127 0.5× 306 1.2× 409 1.6× 130 0.6× 157 0.7× 73 1.0k
Xiaowei Gu United Kingdom 27 147 0.5× 930 3.6× 290 1.1× 143 0.6× 101 0.4× 94 1.8k
Akansha Singh India 21 127 0.5× 285 1.1× 266 1.0× 278 1.2× 129 0.6× 108 1.2k
Pourya Shamsolmoali China 21 334 1.2× 542 2.1× 878 3.4× 111 0.5× 107 0.5× 57 1.8k
Masoumeh Zareapoor China 24 464 1.7× 674 2.6× 825 3.2× 113 0.5× 200 0.9× 58 1.9k

Countries citing papers authored by Weipeng Jing

Since Specialization
Citations

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

Fields of papers citing papers by Weipeng Jing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weipeng Jing

This figure shows the co-authorship network connecting the top 25 collaborators of Weipeng Jing. A scholar is included among the top collaborators of Weipeng Jing 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 Weipeng Jing. Weipeng Jing 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.
Jing, Weipeng, et al.. (2025). Advancing Acer phenology monitoring: fine-grained identification and analysis by deep learning RESformer. Journal of Forestry Research. 36(1). 1 indexed citations
2.
Jing, Weipeng, et al.. (2025). SRF: SpectrumRecombineFormer for Hyperspectral Image Classification. ACM Transactions on Multimedia Computing Communications and Applications. 21(11). 1–25. 2 indexed citations
3.
Gao, Xiang, et al.. (2025). Image Characteristic-Guided Learning Method for Remote-Sensing Image Inpainting. Remote Sensing. 17(13). 2132–2132. 1 indexed citations
4.
Paoletti, Mercedes E., et al.. (2025). A Novel Spectral-Spatial Attention Network for Zero-Shot Pansharpening. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 19805–19820. 1 indexed citations
5.
Zhang, Xiaoyan, et al.. (2025). RSVMamba for Tree Species Classification Using UAV RGB Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–16.
6.
Wu, Zhaoyue, et al.. (2025). KACNet: Kolmogorov-Arnold Convolution Network for Hyperspectral Anomaly Detection. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–14. 6 indexed citations
7.
Chen, Guangsheng, et al.. (2024). GS–CDNet: a remote sensing image cloud detection method with geographic spatial data integration. International Journal of Remote Sensing. 45(24). 9108–9130. 1 indexed citations
8.
Jing, Weipeng, et al.. (2024). Optimized Vectorizing of Building Structures With Switch: High-Efficiency Convolutional Channel-Switch Hybridization Strategy. IEEE Geoscience and Remote Sensing Letters. 21. 1–5. 2 indexed citations
9.
Li, Chao, et al.. (2023). Forest Height Inversion by Convolutional Neural Networks Based on L-Band PolInSAR Data Without Prior Knowledge Dependency. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 10394–10405. 5 indexed citations
10.
Jing, Weipeng, et al.. (2023). Data Augmentation and Few-Shot Change Detection in Forest Remote Sensing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 5919–5934. 13 indexed citations
11.
Jing, Weipeng, et al.. (2022). Binary Neural Network for Multispectral Image Classification. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 6 indexed citations
12.
Chen, Guangsheng, et al.. (2022). Improving the Efficiency of the EMS-Based Smart City: A Novel Distributed Framework for Spatial Data. IEEE Transactions on Industrial Informatics. 19(1). 594–604. 1 indexed citations
13.
Jing, Weipeng, et al.. (2022). Learning holistic and discriminative features via an efficient external memory module for building extraction in remote sensing images. Building and Environment. 222. 109332–109332. 6 indexed citations
14.
Chen, Guangsheng, et al.. (2022). StfMLP: Spatiotemporal Fusion Multilayer Perceptron for Remote-Sensing Images. IEEE Geoscience and Remote Sensing Letters. 20. 1–5. 12 indexed citations
15.
Jing, Weipeng, et al.. (2021). MSAR‐DefogNet: Lightweight cloud removal network for high resolution remote sensing images based on multi scale convolution. IET Image Processing. 16(3). 659–668. 14 indexed citations
16.
Jing, Weipeng, et al.. (2020). Reliability-Aware: Task Scheduling in Cloud Computing Using Multi-Agent Reinforcement Learning Algorithm and Neural Fitted Q. The International Arab Journal of Information Technology. 18(1). 6 indexed citations
17.
Jing, Weipeng, et al.. (2020). Quality Control of the Continuous Hot Pressing Process of Medium Density Fiberboard Using Fuzzy Failure Mode and Effects Analysis. Applied Sciences. 10(13). 4627–4627. 19 indexed citations
18.
Jing, Weipeng, et al.. (2018). Load balancing algorithm for scheduling in heterogeneous cloud. 35(12). 3773–3776. 1 indexed citations
19.
Jing, Weipeng, et al.. (2016). Multiple DAGs dynamic workflow reliability scheduling algorithm in a cloud computing system. 43(2). 88. 1 indexed citations
20.
Jing, Weipeng, et al.. (2012). A reliability task scheduling algorithm with optimizing makespan in heterogeneous systems. World Automation Congress. 409–413. 2 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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