Congcong Wang

1.6k total citations · 1 hit paper
73 papers, 750 citations indexed

About

Congcong Wang is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Congcong Wang has authored 73 papers receiving a total of 750 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 14 papers in Media Technology and 10 papers in Artificial Intelligence. Recurrent topics in Congcong Wang's work include Advanced Image Fusion Techniques (9 papers), Image Enhancement Techniques (8 papers) and Advanced Neural Network Applications (6 papers). Congcong Wang is often cited by papers focused on Advanced Image Fusion Techniques (9 papers), Image Enhancement Techniques (8 papers) and Advanced Neural Network Applications (6 papers). Congcong Wang collaborates with scholars based in China, Norway and France. Congcong Wang's co-authors include David Lillis, Faouzi Alaya Cheikh, Paul Nulty, Jian He, Xiaoping Yang, Jun Ma, Azeddine Beghdadi, Cheng Zhu, Yao Zhang and Song Gu and has published in prestigious journals such as Journal of Personality and Social Psychology, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Congcong Wang

66 papers receiving 727 citations

Hit Papers

AbdomenCT-1K: Is Abdominal Organ Segmentation a Solved Pr... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Congcong Wang China 15 252 213 187 126 89 73 750
Xujing Yao United Kingdom 8 179 0.7× 165 0.8× 201 1.1× 76 0.6× 60 0.7× 11 617
He Zhao China 17 327 1.3× 384 1.8× 380 2.0× 120 1.0× 116 1.3× 50 1.2k
Farhan Riaz Pakistan 16 317 1.3× 127 0.6× 336 1.8× 120 1.0× 73 0.8× 74 1.2k
Jianjia Zhang China 17 249 1.0× 202 0.9× 169 0.9× 206 1.6× 95 1.1× 55 772
Francesco Leporati Italy 16 185 0.7× 221 1.0× 123 0.7× 198 1.6× 164 1.8× 91 914
Xiaoguang Li China 16 404 1.6× 115 0.5× 146 0.8× 56 0.4× 110 1.2× 120 899
Sergio Benini Italy 18 525 2.1× 145 0.7× 173 0.9× 174 1.4× 135 1.5× 61 1.2k
Xi Wu China 16 268 1.1× 244 1.1× 388 2.1× 65 0.5× 43 0.5× 81 974
Tripty Singh India 17 393 1.6× 276 1.3× 346 1.9× 91 0.7× 158 1.8× 141 1.1k
Zifan Wang United States 9 331 1.3× 145 0.7× 449 2.4× 46 0.4× 44 0.5× 18 912

Countries citing papers authored by Congcong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Congcong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Congcong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Congcong Wang. A scholar is included among the top collaborators of Congcong Wang 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 Congcong Wang. Congcong Wang 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.
Li, Yifan, et al.. (2025). Point cloud-based deep learning approach for predicting the tensile properties of steel plates considering random corrosion distribution. Journal of Building Engineering. 104. 112305–112305. 3 indexed citations
2.
Zhao, Meng, et al.. (2025). Adaptive auxiliary diffusion for multi-modal brain tumor segmentation with random missing modalities. Biomedical Signal Processing and Control. 109. 108015–108015.
3.
Wang, Congcong, et al.. (2025). Advancing Interior Design with AI: Controllable Stable Diffusion for Panoramic Image Generation. Buildings. 15(8). 1391–1391.
4.
Wang, Congcong, et al.. (2025). Clinical effectiveness of 3D SPECT/CT imaging in determining osteotomy range for surgical treatment of medication-related osteonecrosis of the jaw: a retrospective study. Journal of Stomatology Oral and Maxillofacial Surgery. 126(5). 102375–102375.
5.
Chen, Jia, Congcong Wang, Fan Shi, et al.. (2024). DSNet: A dynamic squeeze network for real-time weld seam image segmentation. Engineering Applications of Artificial Intelligence. 133. 108278–108278. 9 indexed citations
6.
Wen, Song, Yanyan Li, Chenglin Xu, et al.. (2024). The Relationship Between Computerized Face and Tongue Image Segmentation and Metabolic Parameters in Patients with Type 2 Diabetes Based on Machine Learning. Diabetes Metabolic Syndrome and Obesity. Volume 17. 4049–4068. 2 indexed citations
7.
Cai, Qing, et al.. (2024). Geometry-Enhanced Attentive Multi-View Stereo for Challenging Matching Scenarios. IEEE Transactions on Circuits and Systems for Video Technology. 34(8). 7401–7416. 1 indexed citations
8.
Hao, Xinwei, Hongzhi Zhang, Xiao Wang, et al.. (2024). Synthetic Microbial Community Promotes Bacterial Communities Leading to Soil Multifunctionality in Desertified Land. Microorganisms. 12(6). 1117–1117. 6 indexed citations
9.
10.
Zhao, Meng, et al.. (2023). T-Net: Hierarchical Pyramid Network for Microaneurysm Detection in Retinal Fundus Image. IEEE Transactions on Instrumentation and Measurement. 72. 1–13. 6 indexed citations
11.
Wang, Congcong, et al.. (2022). The MP weak group inverse and its application. Filomat. 36(18). 6085–6102. 7 indexed citations
12.
Luo, Huoling, Congcong Wang, Xingguang Duan, et al.. (2021). Unsupervised learning of depth estimation from imperfect rectified stereo laparoscopic images. Computers in Biology and Medicine. 140. 105109–105109. 17 indexed citations
13.
Mohammed, Ahmed Salih, Congcong Wang, Meng Zhao, et al.. (2020). Weakly-Supervised Network for Detection of COVID-19 in Chest CT Scans. IEEE Access. 8. 155987–156000. 34 indexed citations
14.
Wang, Bo, et al.. (2020). 3D acoustic resolution-based photoacoustic endoscopy with dynamic focusing. Quantitative Imaging in Medicine and Surgery. 11(2). 685–696. 12 indexed citations
15.
Li, Jiatian, Congcong Wang, Chenglin Jia, et al.. (2019). A hybrid conjugate gradient algorithm for solving relative orientation of big rotation angle stereo pair. SHILAP Revista de lepidopterología. 1 indexed citations
16.
Wang, Congcong & David Lillis. (2019). Classification for Crisis-Related Tweets Leveraging Word Embeddings and Data Augmentation.. Research Repository UCD (University College Dublin). 7 indexed citations
17.
Wang, Congcong, et al.. (2018). Deep Smoke Removal from Minimally Invasive Surgery Videos. 3403–3407. 21 indexed citations
18.
Wang, Congcong, et al.. (2017). From ELLs to bilingual teachers: Spanish-english speaking latino teachers’ experiences of language shame & loss. Multicultural education. 24. 16–25. 3 indexed citations
19.
Church, A. Timothy, Marcia S. Katigbak, José de Jesús Vargas‐Flores, et al.. (2014). A four-culture study of self-enhancement and adjustment using the social relations model: Do alternative conceptualizations and indices make a difference?. Journal of Personality and Social Psychology. 106(6). 997–1014. 18 indexed citations
20.
Wang, Congcong. (2008). Improved binary query tree algorithm for anti-collision of RFID tags. Journal of Hefei University of Technology. 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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