Weijie Kong

941 citations
20 papers · 598 indexed · 1 hit paper · h-index 6

Weijie Kong

17 papers receiving 585 citations

Hit Papers

Graph Convolutional Label Noise Cleaner: Train a Plug-And...3762019202620212023100200300

Peers

Weijie Kong
Comparison fields: 5 of 68
  • Computer Vision and Pattern Recognition 272
  • Artificial Intelligence 402
  • Computer Networks and Communications 232
  • Renewable Energy, Sustainability and the Environment 97
  • Biomedical Engineering 124
Replace Xiaopei Wu with:
Xiaopei Wu China
Mohammad Arif Hossain United States
Longbin Chen United States
Chun Shan China
Stephan Herrmann Germany
Chuang Song China
Wenhao He China
Zhao-Qian Chen China
Weijie Kong relative to Xiaopei Wu China Xiaopei Wu's profile →
Citations per field
00.5×7.4×
Xiaopei Wu · 1×
Citations per year

Countries citing papers authored by Weijie Kong

Since Specialization
Citations

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

Fields of papers citing papers by Weijie Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Weijie Kong, 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 Weijie Kong Line = papers co-authored together Weijie Kong links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20254
3 20251
4 20252
5 20250
6 20251
7 20242
8 20247
9 202389
10 202314
11 20230
12 20235
13 20229
14 20223
15 20204
16
Graph Convolutional Label Noise Cleaner: Train a Plug-And-Play Action Classifier for Anomaly Detectionbreakdown →
2019376
17 20191
18 201876
19 20173
20 20131

About Weijie Kong

Weijie Kong is a scholar working on Business and International Management, Renewable Energy, Sustainability and the Environment and General Materials Science, having authored 20 papers that have together received 598 indexed citations. Recurring topics across this work include Electrocatalysts for Energy Conversion (6 papers), Human Pose and Action Recognition (4 papers), Advanced battery technologies research (4 papers), Anomaly Detection Techniques and Applications (4 papers), Multimodal Machine Learning Applications (3 papers), Fuel Cells and Related Materials (2 papers), Catalysis and Hydrodesulfurization Studies (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (272 citations), Artificial Intelligence (402 citations) and Computer Networks and Communications (232 citations). Weijie Kong has collaborated with scholars based in China, Macao and Singapore. Frequent co-authors include Ge Li, Jia-Xing Zhong, Thomas H. Li, Nannan Li, Shan Liu, Fei Lu, Min Zhou, Hangfei Li, Nannan Li and Xin Zhou. Their work appears in journals such as Angewandte Chemie International Edition, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Access.

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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