Jijie Wu

419 citations
13 papers · 265 · h-index 5

Impact in

    • Advanced Neural Network Applications
    • Advanced Image and Video Retrieval Techniques
    • Multimodal Machine Learning Applications
    • Image Processing Techniques and Applications
    • Remote-Sensing Image Classification

Papers in

Jijie Wu

11 papers receiving 265 citations

Peers

Jijie Wu
Comparison fields: 5 of 48
  • Computer Vision and Pattern Recognition 175
  • Media Technology 48
  • Artificial Intelligence 174
  • Radiology, Nuclear Medicine and Imaging 35
  • Biophysics 5
Replace Jingyi Xu with:
Jingyi Xu China
Boyu Yang China
Enrico Fini Italy
Vincent Perot United States
Curtis Wigington United States
Qiufeng Wang China
Zhimao Peng China
Aziz Makandar India
Yingjun Du Netherlands
Jijie Wu relative to Jingyi Xu China Jingyi Xu's profile →
Citations per field
00.5×
Jingyi Xu · 1×
Citations per year

Countries citing papers authored by Jijie Wu

Since Specialization
Citations

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

Fields of papers citing papers by Jijie Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Jijie Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jijie Wu Line = papers co-authored together Jijie Wu links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2020137
2 202352
3 202342
4 202415
5 20207
6 20194
7
Amortized Bayesian Prototype Meta-learning: A New Probabilistic Meta-learning Approach to Few-shot Image Classification
20213
8 20222
9 20211
10 20221
11 20201
12 20240
13 20230

About Jijie Wu

Jijie Wu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Computer Networks and Communications and Media Technology, having authored 13 papers that have together received 265 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (8 papers), Advanced Image and Video Retrieval Techniques (3 papers), COVID-19 diagnosis using AI (3 papers), Advanced Neural Network Applications (3 papers), Robotics and Sensor-Based Localization (2 papers), Multimodal Machine Learning Applications (2 papers), Optimization and Search Problems (2 papers) and Image Processing Techniques and Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (175 citations), Media Technology (48 citations), Artificial Intelligence (174 citations), Radiology, Nuclear Medicine and Imaging (35 citations) and Biophysics (5 citations). Jijie Wu has collaborated with scholars based in China, United Kingdom and Taiwan. Frequent co-authors include Xiaoxu Li, Zhanyu Ma, Jing‐Hao Xue, Jie Cao, Zhuo Sun, Rui Zhu, Qi Song, Dongliang Chang, Yi-Zhe Song and Jun Guo. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, Autonomous Robots, IEEE Transactions on Circuits and Systems for Video Technology and Lanzhou University Institutional Repository.

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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