Ji Wu

540 total citations
13 papers, 397 citations indexed

About

Ji Wu is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Ji Wu has authored 13 papers receiving a total of 397 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Media Technology, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Ji Wu's work include Image Processing Techniques and Applications (6 papers), Digital Holography and Microscopy (4 papers) and Advanced Vision and Imaging (3 papers). Ji Wu is often cited by papers focused on Image Processing Techniques and Applications (6 papers), Digital Holography and Microscopy (4 papers) and Advanced Vision and Imaging (3 papers). Ji Wu collaborates with scholars based in China, Singapore and United Kingdom. Ji Wu's co-authors include Chee Keong Chan, Jianglei Di, Ju Tang, Yu Zhang, Binyu Xiong, Jianlin Zhao, Kaiqiang Wang, Zhenbo Ren, Xiaoyan Wu and Ying Li and has published in prestigious journals such as Renewable Energy, Solar Energy and Optics and Lasers in Engineering.

In The Last Decade

Ji Wu

13 papers receiving 381 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ji Wu China	8	273	242	170	49	43	13	397
Christoph Prahl Germany	16	459 1.7×	134 0.6×	489 2.9×	69 1.4×	87 2.0×	39	672
J.A. Jervase Oman	10	420 1.5×	358 1.5×	420 2.5×	35 0.7×	6 0.1×	32	706
Bijan Nouri Germany	16	577 2.1×	86 0.4×	435 2.6×	23 0.5×	104 2.4×	55	704
Ben Kurtz United States	11	423 1.5×	158 0.7×	294 1.7×	7 0.1×	48 1.1×	15	517
Baptiste Schubnel Switzerland	9	177 0.6×	204 0.8×	68 0.4×	44 0.9×	5 0.1×	21	330
Salomé Ndjakomo Essiane Cameroon	9	150 0.5×	158 0.7×	183 1.1×	28 0.6×	4 0.1×	42	343
Ping Fang China	8	118 0.4×	264 1.1×	14 0.1×	32 0.7×	16 0.4×	25	386
B. Urquhart United States	10	994 3.6×	393 1.6×	683 4.0×	11 0.2×	127 3.0×	11	1.1k
Daniel Riley United States	14	304 1.1×	334 1.4×	421 2.5×	27 0.6×	6 0.1×	46	610
Zeyuan Yu China	8	158 0.6×	325 1.3×	17 0.1×	12 0.2×	35 0.8×	28	503

Countries citing papers authored by Ji Wu

Since Specialization

Citations

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

Fields of papers citing papers by Ji Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ji Wu

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

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Wu, Ji, Ju Tang, Mengmeng Zhang, et al.. (2022). PredictionNet: a long short-term memory-based attention network for atmospheric turbulence prediction in adaptive optics. Applied Optics. 61(13). 3687–3687. 13 indexed citations

2.

Wu, Ji, Ju Tang, Jiawei Zhang, & Jianglei Di. (2022). Coherent noise suppression in digital holographic microscopy based on label-free deep learning. Frontiers in Physics. 10. 8 indexed citations

3.

Tang, Ju, Jiawei Zhang, Ji Wu, Jianglei Di, & Jianlin Zhao. (2022). Coherent Noise Suppression of Single-Shot Digital Holographic Phase Via an Untrained Self-Supervised Network. 3. 3 indexed citations

4.

Tang, Ju, Ji Wu, Jiawei Zhang, et al.. (2021). Single-Shot Diffraction Autofocusing: Distance Prediction via an Untrained Physics-Enhanced Network. IEEE photonics journal. 14(1). 1–6. 10 indexed citations

5.

Di, Jianglei, Ji Wu, Kaiqiang Wang, et al.. (2021). Quantitative Phase Imaging Using Deep Learning-Based Holographic Microscope. Frontiers in Physics. 9. 17 indexed citations

6.

Tang, Ju, Ji Wu, Kaiqiang Wang, et al.. (2021). RestoreNet-Plus: Image restoration via deep learning in optical synthetic aperture imaging system. Optics and Lasers in Engineering. 146. 106707–106707. 17 indexed citations

7.

Wu, Ji. (2015). Homoploid Hybridization between Native Salix cavaleriei and Exotic Salix matsudana(Salicaceae). 2 indexed citations

8.

Wu, Ji, et al.. (2013). Prediction of solar radiation with genetic approach combing multi-model framework. Renewable Energy. 66. 132–139. 50 indexed citations

9.

Wu, Ji & Chee Keong Chan. (2012). The Prediction of Monthly Average Solar Radiation with TDNN and ARIMA. DR-NTU (Nanyang Technological University). 469–474. 19 indexed citations

10.

Wu, Ji, et al.. (2011). Prediction of hourly solar radiation using a novel hybrid model of ARMA and TDNN. Solar Energy. 85(5). 808–817. 249 indexed citations

11.

Zhang, Cheng & Ji Wu. (2006). Near field 3D scene simulation for passive microwave imaging. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6419. 641902–641902. 4 indexed citations

12.

Zhou, Huiyu, Tangwei Liu, Huosheng Hu, et al.. (2006). A hybrid framework for image segmentation. 2. 749–752. 4 indexed citations

13.

Liu, Tangwei, Huiyu Zhou, Faquan Lin, Yusheng Pang, & Ji Wu. (2005). Image denoising and detail preservation by probabilistic models. 63. 285–290. 1 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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