Mengqi Ji

863 total citations
24 papers, 360 citations indexed

About

Mengqi Ji is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Oncology. According to data from OpenAlex, Mengqi Ji has authored 24 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 5 papers in Cognitive Neuroscience and 3 papers in Oncology. Recurrent topics in Mengqi Ji's work include Advanced Vision and Imaging (8 papers), Image Enhancement Techniques (5 papers) and Advanced Image Processing Techniques (4 papers). Mengqi Ji is often cited by papers focused on Advanced Vision and Imaging (8 papers), Image Enhancement Techniques (5 papers) and Advanced Image Processing Techniques (4 papers). Mengqi Ji collaborates with scholars based in China, Hong Kong and United States. Mengqi Ji's co-authors include Lu Fang, Haitian Zheng, Eckehard Steinbach, Matti Strese, Qionghai Dai, Xiaoyun Yuan, Lu Fang, Jiamin Wu, Junpeng Zhang and Yan Zhao and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.

In The Last Decade

Mengqi Ji

21 papers receiving 352 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mengqi Ji China	11	173	61	60	57	56	24	360
Fan Zhong China	14	386 2.2×	14 0.2×	31 0.5×	46 0.8×	31 0.6×	50	500
Yasuyo Kita Japan	14	280 1.6×	23 0.4×	16 0.3×	113 2.0×	77 1.4×	58	510
Beiji Zou China	11	207 1.2×	14 0.2×	71 1.2×	57 1.0×	26 0.5×	50	365
Toufique Ahmed Soomro Pakistan	18	566 3.3×	13 0.2×	67 1.1×	171 3.0×	105 1.9×	46	1.1k
Wenju Xu United States	10	247 1.4×	13 0.2×	25 0.4×	96 1.7×	70 1.3×	21	437
Kiyohide Satoh Japan	13	352 2.0×	13 0.2×	24 0.4×	11 0.2×	43 0.8×	21	451
Linlin Wang China	13	298 1.7×	14 0.2×	143 2.4×	16 0.3×	35 0.6×	44	453
Kurtis Keller United States	10	349 2.0×	70 1.1×	176 2.9×	13 0.2×	89 1.6×	14	603
Hyunjae Lee South Korea	9	140 0.8×	13 0.2×	28 0.5×	96 1.7×	38 0.7×	28	374

Countries citing papers authored by Mengqi Ji

Since Specialization

Citations

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

Fields of papers citing papers by Mengqi Ji

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mengqi Ji

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

All Works

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20 of 20 papers shown

Zhong, Fan, Mengqi Ji, Jianru Chen, et al.. (2024). Optimizing vitiligo diagnosis with ResNet and Swin transformer deep learning models: a study on performance and interpretability. Scientific Reports. 14(1). 9127–9127. 9 indexed citations

Zhong, Fan, et al.. (2024). An Enhanced Segmentation Method of Dermatological Images Based on DeepLabV3+ with Dual Attention Mechanism. 1–7.

Pu, Shiliang, et al.. (2024). Visible and near‐infrared image fusion based on information complementarity. CAAI Transactions on Intelligence Technology. 10(1). 193–206.

Shi, Yujie, Mengqi Ji, Fan Zhong, et al.. (2024). Resting-state EEG microstate analysis reveals potential biomarkers for subclinical insomnia. SHILAP Revista de lepidopterología. 3(1).

Zhang, Junpeng, et al.. (2023). Recent Advancements and Perspectives in the Diagnosis of Skin Diseases Using Machine Learning and Deep Learning: A Review. Diagnostics. 13(23). 3506–3506. 27 indexed citations

Wang, Xueyang, et al.. (2023). The Group Interaction Field for Learning and Explaining Pedestrian Anticipation. Engineering. 34. 70–82. 5 indexed citations

Ji, Mengqi, et al.. (2022). Surface Material Perception Through Multimodal Learning. IEEE Journal of Selected Topics in Signal Processing. 16(4). 843–853. 3 indexed citations

Feng, Jingwen, Yujie Shi, Xiaojing Li, et al.. (2022). Automated Rest EEG-Based Diagnosis of Depression and Schizophrenia Using a Deep Convolutional Neural Network. IEEE Access. 10. 104472–104485. 12 indexed citations

Ji, Mengqi, et al.. (2021). SurRF: Unsupervised Multi-View Stereopsis by Learning Surface Radiance Field. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(11). 7912–7927. 7 indexed citations

10.

Ji, Mengqi, et al.. (2021). Boosting Single Image Super-Resolution Learnt From Implicit Multi-Image Prior. IEEE Transactions on Image Processing. 30. 3240–3251. 3 indexed citations

11.

Zhang, Jianing, Mengqi Ji, Guangyu Wang, et al.. (2021). GigaMVS: A Benchmark for Ultra-Large-Scale Gigapixel-Level 3D Reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(11). 7534–7550. 14 indexed citations

12.

Yuan, Xiaoyun, Mengqi Ji, Jiamin Wu, et al.. (2021). A modular hierarchical array camera. Light Science & Applications. 10(1). 37–37. 33 indexed citations

13.

Ji, Mengqi, Rongpin Wang, Xinfeng Liu, et al.. (2020). A Learning-Based Model to Evaluate Hospitalization Priority in COVID-19 Pandemics. Patterns. 1(9). 100173–100173. 4 indexed citations

14.

Ji, Mengqi, Rongpin Wang, Xinfeng Liu, et al.. (2020). A Learning-Based Model to Evaluate Hospitalization Priority in COVID-19 Pandemics. Patterns. 1(6). 100092–100092. 18 indexed citations

15.

Ji, Mengqi, et al.. (2020). SurfaceNet+: An End-to-end 3D Neural Network for Very Sparse Multi-View Stereopsis. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(11). 4078–4093. 24 indexed citations

16.

Zhao, Yaping, et al.. (2020). Zoom in to the Details of Human-Centric Videos. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3089–3093. 6 indexed citations

17.

Ji, Mengqi, Shengwei Jiang, Xukang Wang, et al.. (2020). Augmenting vascular disease diagnosis by vasculature-aware unsupervised learning. Nature Machine Intelligence. 2(6). 337–346. 16 indexed citations

18.

Zheng, Haitian, et al.. (2017). Learning Cross-scale Correspondence and Patch-based Synthesis for Reference-based Super-Resolution. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 45 indexed citations

19.

Ji, Mengqi, Lu Fang, Haitian Zheng, Matti Strese, & Eckehard Steinbach. (2015). Preprocessing-free surface material classification using convolutional neural networks pretrained by sparse Autoencoder. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1–6. 15 indexed citations

20.

Yang, Haiyan, Oscar C. Au, Jin Zeng, et al.. (2014). A comprehensive study on digital image matting. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 6. 286–290. 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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