Xi Wu

1.6k citations
81 papers · 974 · 1 hit paper · h-index 16

Impact in

Papers in

Xi Wu

74 papers receiving 934 citations

Xi Wu's Hit Papers

Target-Dependent Sentiment Classification With BERT 2019 · 295 citations
2950+2+4Years since publication50100150200250

Peers

Xi Wu
Comparison fields: 5 of 129
  • Computer Vision and Pattern Recognition 268
  • Artificial Intelligence 388
  • Radiology, Nuclear Medicine and Imaging 244
  • Computational Mathematics 6
  • Otorhinolaryngology 41
Replace Jiliu Zhou with:
Jiliu Zhou China
Chen Zu China
Hongyu Wang China
Melissa Berthelot United Kingdom
Xu Sun China
Dazhe Zhao China
Piotr A. Habas United States
Jinzhu Yang China
Ali Mottaghi United States
Maryam Panahiazar United States
Xi Wu relative to Jiliu Zhou China Jiliu Zhou's profile →
Citations per field
00.5×1.5×
Jiliu Zhou · 1×
Citations per year

Countries citing papers authored by Xi Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xi Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Target-Dependent Sentiment Classification With BERT
Hit paper breakdown →
2019295
2 202272
3 201747
4 201836
5 201829
6 202327
7 201026
8 201526
9 201925
10 200922
11 202022
12 202020
13 202019
14
Deep Learning intra-image and inter-images features for Co-saliency detection.
201816
15 201816
16 201315
17 201715
18 202014
19 201211
20 202110

About Xi Wu

Xi Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Neurology, having authored 81 papers that have together received 974 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (12 papers), Advanced Neuroimaging Techniques and Applications (12 papers), Medical Image Segmentation Techniques (12 papers), Image and Signal Denoising Methods (9 papers), Advanced MRI Techniques and Applications (8 papers), Advanced Image Processing Techniques (8 papers), Functional Brain Connectivity Studies (8 papers) and Domain Adaptation and Few-Shot Learning (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (268 citations), Artificial Intelligence (388 citations), Radiology, Nuclear Medicine and Imaging (244 citations), Computational Mathematics (6 citations) and Otorhinolaryngology (41 citations). Xi Wu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Ao Feng, Zhengjie Gao, Xinyu Song, Jiliu Zhou, Zhaohua Ding, John C. Gore, Dong Nie, Zhipeng Yang, Yan Wang and Jiliu Zhou. Their work appears in journals such as IEEE Access, Medical Physics, Neurocomputing, Soft Computing and Knowledge-Based Systems.

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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