Zhaopeng Tu

6.7k total citations
112 papers, 2.6k citations indexed

About

Zhaopeng Tu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Zhaopeng Tu has authored 112 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 101 papers in Artificial Intelligence, 52 papers in Computer Vision and Pattern Recognition and 6 papers in Molecular Biology. Recurrent topics in Zhaopeng Tu's work include Natural Language Processing Techniques (93 papers), Topic Modeling (92 papers) and Multimodal Machine Learning Applications (44 papers). Zhaopeng Tu is often cited by papers focused on Natural Language Processing Techniques (93 papers), Topic Modeling (92 papers) and Multimodal Machine Learning Applications (44 papers). Zhaopeng Tu collaborates with scholars based in China, Hong Kong and United States. Zhaopeng Tu's co-authors include Shuming Shi, Longyue Wang, Yang Liu, Prémkumar Dévanbu, Tong Zhang, Xing Wang, Baosong Yang, Michael R. Lyu, Zhendong Su and Derek F. Wong and has published in prestigious journals such as SHILAP Revista de lepidopterología, Artificial Intelligence and Neurocomputing.

In The Last Decade

Zhaopeng Tu

103 papers receiving 2.5k citations

Peers

Zhaopeng Tu
Comparison fields: 5 of 116
  • Artificial Intelligence 2.1k
  • Computer Vision and Pattern Recognition 870
  • Information Systems 432
  • Software 207
  • Signal Processing 143
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Citations per field, relative to Zhaopeng Tu
Zhaopeng Tu · 1×
Citations per year, relative to Zhaopeng Tu
Zhaopeng Tu · 1×

Countries citing papers authored by Zhaopeng Tu

Since Specialization
Citations

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

Fields of papers citing papers by Zhaopeng Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhaopeng Tu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhaopeng Tu. A scholar is included among the top collaborators of Zhaopeng Tu 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 Zhaopeng Tu. Zhaopeng Tu 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
# Work Indexed citations
1 48
2 0
3 4
4 10
5 2
6 2
7 2
8 12
9
Understanding and Improving Lexical Choice in Non-Autoregressive Translation
12
10 3
11 104
12
Semantics-Enhanced Task-Oriented Dialogue Translation: A Case Study on Hotel Booking
5
13 160
14
Coverage-based Neural Machine Translation.
37
15
A Novel Graph-based Compact Representation of Word Alignment
0
16
Head-Driven Hierarchical Phrase-based Translation
7
17
Combining Multiple Alignments to Improve Machine Translation
11
18
Using Syntactic Head Information in Hierarchical Phrase-Based Translation
8
19
Extracting Hierarchical Rules from a Weighted Alignment Matrix
5
20 15

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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