Wanting Ji

887 total citations
37 papers, 632 citations indexed

About

Wanting Ji is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Wanting Ji has authored 37 papers receiving a total of 632 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 7 papers in Information Systems. Recurrent topics in Wanting Ji's work include Human Pose and Action Recognition (6 papers), Multimodal Machine Learning Applications (5 papers) and Speech and Audio Processing (4 papers). Wanting Ji is often cited by papers focused on Human Pose and Action Recognition (6 papers), Multimodal Machine Learning Applications (5 papers) and Speech and Audio Processing (4 papers). Wanting Ji collaborates with scholars based in China, New Zealand and Finland. Wanting Ji's co-authors include Ruili Wang, Ming Zong, Mingzhe Liu, Xun Wang, Hao Zheng, Wai Keung Wong, Zhihui Lai, Xiaoyun Jia, Yan Tian and Changan Yuan and has published in prestigious journals such as PLoS ONE, Scientific Reports and Information Sciences.

In The Last Decade

Wanting Ji

36 papers receiving 611 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wanting Ji China	15	358	211	74	68	61	37	632
Aznul Qalid Md Sabri Malaysia	15	173 0.5×	252 1.2×	58 0.8×	72 1.1×	61 1.0×	44	697
Young-Tack Park South Korea	8	249 0.7×	210 1.0×	61 0.8×	32 0.5×	40 0.7×	48	503
Ilya Makarov Russia	15	377 1.1×	270 1.3×	43 0.6×	23 0.3×	64 1.0×	99	802
Kamlesh Mistry United Kingdom	10	309 0.9×	304 1.4×	35 0.5×	56 0.8×	68 1.1×	27	733
J. Samuel Manoharan India	13	205 0.6×	214 1.0×	73 1.0×	40 0.6×	36 0.6×	35	607
Yafang Wang China	14	177 0.5×	221 1.0×	111 1.5×	50 0.7×	39 0.6×	51	578
Jianming Lv China	14	290 0.8×	221 1.0×	51 0.7×	63 0.9×	77 1.3×	48	664
Xinhan Wang China	12	189 0.5×	191 0.9×	66 0.9×	102 1.5×	37 0.6×	23	662
Faliang Huang China	13	152 0.4×	396 1.9×	133 1.8×	27 0.4×	37 0.6×	50	702
T Anjali India	14	131 0.4×	94 0.4×	55 0.7×	34 0.5×	61 1.0×	117	554

Countries citing papers authored by Wanting Ji

Since Specialization

Citations

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

Fields of papers citing papers by Wanting Ji

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wanting Ji

This figure shows the co-authorship network connecting the top 25 collaborators of Wanting Ji. A scholar is included among the top collaborators of Wanting Ji 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 Wanting Ji. Wanting Ji 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:

20 of 20 papers shown

Hu, Yilong, Wanting Ji, Sijie Wang, et al.. (2025). Sustained Activation of Nrf2 Antioxidant Pathway by Flexible Liposome Based on Low Phase Transition Temperature to Delay Skin Aging. Advanced Healthcare Materials. 15(3). e01696–e01696.

Ji, Wanting, et al.. (2024). Local instance-based transfer learning for reinforcement learning. Engineering Applications of Artificial Intelligence. 133. 108488–108488. 6 indexed citations

Zhang, Haolin, et al.. (2024). Multi-source heterogeneous blockchain data quality assessment model for enterprise business activities. PLoS ONE. 19(6). e0304835–e0304835. 2 indexed citations

Ji, Wanting, et al.. (2024). A hybrid storage blockchain-based query efficiency enhancement method for business environment evaluation. Knowledge and Information Systems. 66(10). 6307–6335. 1 indexed citations

Ji, Wanting, et al.. (2023). Fine-grained document-level financial event argument extraction approach. Engineering Applications of Artificial Intelligence. 121. 105943–105943. 5 indexed citations

Wang, Ruili, et al.. (2023). Convolutional transformer network for fine-grained action recognition. Neurocomputing. 569. 127027–127027. 14 indexed citations

Ji, Wanting, et al.. (2023). Author Correction to: A composite blockchain associated event traceability method for financial activities. Peer-to-Peer Networking and Applications. 17(1). 567–568. 1 indexed citations

Ji, Wanting, et al.. (2023). A composite blockchain associated event traceability method for financial activities. Peer-to-Peer Networking and Applications. 16(4). 1696–1715. 2 indexed citations

Chen, Ze, et al.. (2023). Document-level multi-task learning approach based on coreference-aware dynamic heterogeneous graph network for event extraction. Neural Computing and Applications. 36(1). 303–321. 3 indexed citations

10.

Ji, Wanting, et al.. (2022). A T-CNN time series classification method based on Gram matrix. Scientific Reports. 12(1). 15731–15731. 11 indexed citations

11.

Wang, Ruili, Feng Hou, Steven F. Cahan, et al.. (2022). Fine-Grained Entity Typing with a Type Taxonomy: a Systematic Review. IEEE Transactions on Knowledge and Data Engineering. 1–1. 9 indexed citations

12.

Zong, Ming, et al.. (2022). Spatial and temporal saliency based four-stream network with multi-task learning for action recognition. Applied Soft Computing. 132. 109884–109884. 28 indexed citations

13.

Ji, Wanting, et al.. (2022). Multi-head attention-based two-stream EfficientNet for action recognition. Multimedia Systems. 29(2). 487–498. 28 indexed citations

14.

Ji, Wanting, Ruili Wang, Yan Tian, & Xun Wang. (2021). An attention based dual learning approach for video captioning. Applied Soft Computing. 117. 108332–108332. 27 indexed citations

15.

Ji, Wanting, et al.. (2021). A Scene-Dependent Sound Event Detection Approach Using Multi-Task Learning. IEEE Sensors Journal. 22(18). 17483–17489. 9 indexed citations

16.

Qian, Lingyun, Wanting Ji, Chaoyang Sun, Gang Fang, & Junhe Lian. (2021). Prediction of edge fracture during hole-flanging of advanced high-strength steel considering blanking pre-damage. Engineering Fracture Mechanics. 248. 107721–107721. 23 indexed citations

17.

Ji, Wanting, et al.. (2021). Fuzzy rough sets and fuzzy rough neural networks for feature selection: A review. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 11(3). 42 indexed citations

18.

Zheng, Hao, Ruili Wang, Wanting Ji, et al.. (2020). Discriminative deep multi-task learning for facial expression recognition. Information Sciences. 533. 60–71. 69 indexed citations

19.

Liu, Zhenbing, et al.. (2020). Spatiotemporal saliency-based multi-stream networks with attention-aware LSTM for action recognition. Neural Computing and Applications. 32(18). 14593–14602. 38 indexed citations

20.

Ji, Wanting, et al.. (2016). Similarity nodes query algorithm on large dynamic graph based on the snapshots. 36(2). 358–363. 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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