Junding Sun

2.3k total citations
90 papers, 1.5k citations indexed

About

Junding Sun is a scholar working on Computer Vision and Pattern Recognition, Neurology and Artificial Intelligence. According to data from OpenAlex, Junding Sun has authored 90 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Computer Vision and Pattern Recognition, 25 papers in Neurology and 22 papers in Artificial Intelligence. Recurrent topics in Junding Sun's work include Advanced Image and Video Retrieval Techniques (28 papers), Image Retrieval and Classification Techniques (27 papers) and Brain Tumor Detection and Classification (25 papers). Junding Sun is often cited by papers focused on Advanced Image and Video Retrieval Techniques (28 papers), Image Retrieval and Classification Techniques (27 papers) and Brain Tumor Detection and Classification (25 papers). Junding Sun collaborates with scholars based in China, United Kingdom and Saudi Arabia. Junding Sun's co-authors include Yudong Zhang, Chaosheng Tang, Shuihua Wang‎, Xiaosheng Wu, Preetha Phillips, Guihu Zhao, Vishnuvarthanan Govindaraj, Wei‐Guo Zhu, Yuxiu Sui and Lihua Zhou and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Junding Sun

80 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junding Sun China 18 612 462 358 320 146 90 1.5k
Fatih Özyurt Türkiye 15 779 1.3× 723 1.6× 398 1.1× 640 2.0× 154 1.1× 63 1.6k
Kaijian Xia China 19 399 0.7× 401 0.9× 165 0.5× 259 0.8× 137 0.9× 94 1.3k
Shihui Ying China 24 1.0k 1.7× 670 1.5× 265 0.7× 435 1.4× 184 1.3× 124 2.2k
Qinghua Zhou China 17 372 0.6× 372 0.8× 156 0.4× 336 1.1× 93 0.6× 48 1.3k
Xiang Yu China 17 599 1.0× 570 1.2× 164 0.5× 456 1.4× 86 0.6× 49 1.6k
Deepak Ranjan Nayak India 26 723 1.2× 908 2.0× 540 1.5× 760 2.4× 150 1.0× 74 2.0k
Ümit Budak Türkiye 21 517 0.8× 602 1.3× 158 0.4× 542 1.7× 67 0.5× 42 1.6k
Majed Alhaisoni Saudi Arabia 29 875 1.4× 1.0k 2.2× 574 1.6× 671 2.1× 102 0.7× 104 2.5k
Şaban Öztürk Türkiye 23 537 0.9× 570 1.2× 107 0.3× 456 1.4× 91 0.6× 63 1.6k

Countries citing papers authored by Junding Sun

Since Specialization
Citations

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

Fields of papers citing papers by Junding Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junding Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Junding Sun. A scholar is included among the top collaborators of Junding Sun 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 Junding Sun. Junding Sun 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.
Tang, Chaosheng, et al.. (2025). Diff‐ CFFBNet : Diffusion‐Embedded Cross‐Layer Feature Fusion Bridge Network for Brain Tumor Segmentation. International Journal of Imaging Systems and Technology. 35(3). 1 indexed citations
2.
Sun, Junding, et al.. (2025). MSM-UNet: A medical image segmentation method based on wavelet transform and multi-scale Mamba-UNet. Expert Systems with Applications. 288. 128241–128241. 1 indexed citations
3.
Sun, Junding, et al.. (2025). DCMA-Net: A dual channel multi-scale feature attention network for crack image segmentation. Engineering Applications of Artificial Intelligence. 148. 110411–110411. 2 indexed citations
4.
Sun, Junding, S. P. Wen, Chaosheng Tang, et al.. (2025). C-HGDAT: Hypergraph dynamic attention network with CNN-Driven features for brain tumor classification. Biomedical Signal Processing and Control. 112. 108747–108747.
5.
Sun, Junding, et al.. (2025). DGFE-Mamba: Mamba-Based 2D Image Segmentation Network. Journal of Bionic Engineering. 22(4). 2135–2150.
6.
Sun, Junding, et al.. (2024). CasUNeXt: A Cascaded Transformer With Intra‐ and Inter‐Scale Information for Medical Image Segmentation. International Journal of Imaging Systems and Technology. 34(5).
7.
Tang, Chaosheng, et al.. (2024). Lung-YOLO: Multiscale feature fusion attention and cross-layer aggregation for lung nodule detection. Biomedical Signal Processing and Control. 99. 106815–106815. 5 indexed citations
8.
Tang, Chaosheng, et al.. (2024). TGPO-WRHNN: Two-stage Grad-CAM-guided PMRS Optimization and weighted-residual hypergraph neural network for pneumonia detection. Knowledge-Based Systems. 306. 112708–112708. 2 indexed citations
9.
Gao, Feng, et al.. (2023). Collaborative optimization of spatial-spectrum parallel convolutional network (CO-PCN) for hyperspectral image classification. International Journal of Machine Learning and Cybernetics. 14(7). 2353–2366. 2 indexed citations
10.
Wu, Xiaosheng, Qihong Yang, Chao‐Sheng Tang, & Junding Sun. (2023). Multimodal Brain Tumor MR Image Segmentation Network Fused with Attention Mechanism. Journal of Computer-Aided Design & Computer Graphics. 35(9). 1429–1438.
11.
Sun, Junding, et al.. (2023). CTMLP: Can MLPs replace CNNs or transformers for COVID-19 diagnosis?. Computers in Biology and Medicine. 159. 106847–106847. 2 indexed citations
12.
Xu, Zhaozhao, et al.. (2023). FG-HFS: A feature filter and group evolution hybrid feature selection algorithm for high-dimensional gene expression data. Expert Systems with Applications. 245. 123069–123069. 19 indexed citations
13.
Tang, Chaosheng, et al.. (2023). CsAGP: Detecting Alzheimer's disease from multimodal images via dual-transformer with cross-attention and graph pooling. Journal of King Saud University - Computer and Information Sciences. 35(7). 101618–101618. 24 indexed citations
14.
Sun, Junding, et al.. (2022). TSRNet: Diagnosis of COVID-19 based on self-supervised learning and hybrid ensemble model. Computers in Biology and Medicine. 146. 105531–105531. 5 indexed citations
15.
Tang, Chaosheng, et al.. (2022). BraDect: A Novel Brain Tumor Image Classification Algorithm. 12–17. 1 indexed citations
16.
Tang, Chaosheng, et al.. (2022). NSCGCN: A novel deep GCN model to diagnosis COVID-19. Computers in Biology and Medicine. 150. 106151–106151. 13 indexed citations
17.
Tang, Chaosheng, et al.. (2021). Deep learning-based medical images analysis evolved from convolution to graph convolution. Journal of Image and Graphics. 26(9). 2078–2093. 1 indexed citations
18.
Sun, Junding, et al.. (2021). MFBCNNC: Momentum factor biogeography convolutional neural network for COVID-19 detection via chest X-ray images. Knowledge-Based Systems. 232. 107494–107494. 16 indexed citations
19.
Sun, Junding, et al.. (2020). Face Recognition Based on Local Gradient Number Pattern and Fuzzy Convex-Concave Partition. IEEE Access. 8. 35777–35791. 8 indexed citations
20.
Sun, Junding, et al.. (2010). Image retrieval based on color and texture features. Computer Engineering and Applications Journal. 46(29). 176–178. 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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