Jiahua Dong

2.5k total citations · 1 hit paper
49 papers, 1.5k citations indexed

About

Jiahua Dong is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Jiahua Dong has authored 49 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 27 papers in Artificial Intelligence and 4 papers in Cognitive Neuroscience. Recurrent topics in Jiahua Dong's work include Domain Adaptation and Few-Shot Learning (21 papers), Advanced Neural Network Applications (9 papers) and Multimodal Machine Learning Applications (7 papers). Jiahua Dong is often cited by papers focused on Domain Adaptation and Few-Shot Learning (21 papers), Advanced Neural Network Applications (9 papers) and Multimodal Machine Learning Applications (7 papers). Jiahua Dong collaborates with scholars based in China, United States and Hong Kong. Jiahua Dong's co-authors include Gan Sun, Yang Cong, Zhengming Ding, Zhen Fang, Qiang Wang, Xiaowei Xu, Shujun Cao, Huimin Wang, Yong Ling and Lingjuan Lyu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Frontiers in Microbiology.

In The Last Decade

Jiahua Dong

45 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

MM-LLMs: Recent Advances in MultiModal Large Language Models

2024 87 citations Jiahua Dong, Chenhui Chu et al. profile →

Peers

Jiahua Dong

AI

CVPR

AE

MB

RNMI

Mingliang Zhou China

Hantao Yao China

Lianglun Cheng China

Jianwei Zhao China

Parvathaneni Naga Srinivasu India

Yangming Li China

Hang Yu China

Suk‐Hwan Lee South Korea

Xia Chen China

Mingliang Zhou China

Jiahua Dong

119 ×0.2

AI

879 ×1.7

CVPR

93 ×0.8

AE

32 ×0.3

MB

30 ×0.3

RNMI

Citations per year, relative to Jiahua Dong Jiahua Dong (= 1×) peers Mingliang Zhou

Countries citing papers authored by Jiahua Dong

Since Specialization

Citations

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

Fields of papers citing papers by Jiahua Dong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiahua Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Jiahua Dong. A scholar is included among the top collaborators of Jiahua Dong 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 Jiahua Dong. Jiahua Dong 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

1.

Liu, Yang, et al.. (2025). Step-by-step to success: Multi-stage learning driven robust audiovisual fusion network for fine-grained bird species classification. Avian Research. 16(4). 100280–100280.

2.

Zhang, Duzhen, et al.. (2025). Federated Incremental Named Entity Recognition. IEEE Transactions on Audio Speech and Language Processing. 33. 1551–1562.

3.

Zhang, Duzhen, Zhongzhi Li, Mingliang Zhang, et al.. (2025). From System 1 to System 2: A Survey of Reasoning Large Language Models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(3). 3335–3354.

4.

Sun, Gan, et al.. (2025). MuseumMaker: Continual Style Customization Without Catastrophic Forgetting. IEEE Transactions on Image Processing. 34. 2499–2512. 2 indexed citations

5.

Dong, Jiahua, et al.. (2024). MM-LLMs: Recent Advances in MultiModal Large Language Models. 12401–12430. 87 indexed citations breakdown →

6.

Dong, Jiahua, Albert Bode, Rob Kooper, et al.. (2024). Accurate Feature Extraction from Historical Geologic Maps Using Open-Set Segmentation and Detection. Geosciences. 14(11). 305–305. 1 indexed citations

7.

Zhang, Yinlong, et al.. (2024). LinK3D: Linear Keypoints Representation for 3D LiDAR Point Cloud. IEEE Robotics and Automation Letters. 9(3). 2128–2135. 31 indexed citations

8.

Huang, Chun-Rong, et al.. (2024). Epiphytic zooplankton community profiles in a typical urban wetland as revealed by DNA metabarcoding. Journal of Oceanology and Limnology. 42(5). 1571–1585. 1 indexed citations

9.

Zhang, Duzhen, et al.. (2023). Task Relation Distillation and Prototypical Pseudo Label for Incremental Named Entity Recognition. 3319–3329. 8 indexed citations

10.

Dong, Jiahua, et al.. (2023). Urban Cultural Inheritance: Generative Adversarial Networks (GANs) Assisted Street Facade Design in Virtual Reality (VR) Environments Based on Hakka Settlements in Hong Kong. Proceedings of the International Conference on Computer-Aided Architectural Design Research in Asia. 1. 473–482. 1 indexed citations

11.

Zhang, Duzhen, et al.. (2023). Continual Named Entity Recognition without Catastrophic Forgetting. 8186–8197. 6 indexed citations

12.

Cong, Yang, et al.. (2023). Gradient-Semantic Compensation for Incremental Semantic Segmentation. IEEE Transactions on Multimedia. 26. 5561–5574. 7 indexed citations

13.

Cong, Yang, et al.. (2023). Open-Ended Online Learning for Autonomous Visual Perception. IEEE Transactions on Neural Networks and Learning Systems. 35(8). 10178–10198. 5 indexed citations

14.

Huang, Chun-Rong, et al.. (2022). High-throughput sequencing reveals omnivorous and preferential diets of the rotifer Polyarthra in situ. Frontiers in Microbiology. 13. 1048619–1048619. 4 indexed citations

15.

Ren, Yu, Yang Cong, Jiahua Dong, & Gan Sun. (2022). Uni3DA: Universal 3D Domain Adaptation for Object Recognition. IEEE Transactions on Circuits and Systems for Video Technology. 33(1). 379–392. 8 indexed citations

16.

Dong, Jiahua, et al.. (2021). Confident Anchor-Induced Multi-Source Free Domain Adaptation. Neural Information Processing Systems. 34. 28 indexed citations

17.

Zhang, Tao, Yang Cong, Gan Sun, & Jiahua Dong. (2021). Visual–Tactile Fused Graph Learning for Object Clustering. IEEE Transactions on Cybernetics. 52(11). 12275–12289. 17 indexed citations

18.

Hou, Dongdong, et al.. (2020). Fast Multi-View Outlier Detection via Deep Encoder. IEEE Transactions on Big Data. 8(4). 1047–1058. 6 indexed citations

19.

Cao, Shujun, et al.. (2019). Nanoparticles: Oral Delivery for Protein and Peptide Drugs. AAPS PharmSciTech. 20(5). 190–190. 219 indexed citations

20.

Dong, Jiahua, et al.. (2017). A Note on Implicit Fractional Differential Equations. 7(3). 261–267. 7 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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