Yiqiao Mao

445 citations
16 papers · 294 indexed · 1 hit paper · h-index 6
Topics
Domain Adaptation and Few-Shot Learning (7 papers)Advanced Image and Video Retrieval Techniques (6 papers)Video Analysis and Summarization (4 papers)
Partner nations
ChinaUnited KingdomMacao

In The Last Decade

Yiqiao Mao

11 papers receiving 291 citations

Hit Papers

Deep multi-view learning methods: A review2021202620222024202150100150

Peers

Yiqiao Mao
Comparison fields: 5 of 82
  • Artificial Intelligence 155
  • Computer Vision and Pattern Recognition 152
  • Media Technology 26
  • Signal Processing 24
  • Radiology, Nuclear Medicine and Imaging 18
Replace Jaeyoon Yoo with:
Jaeyoon Yoo South Korea
Huidong Liu China
Nanyang Ye China
Zhi Gao China
Yongjun Hong South Korea
Vivek Sharma Germany
Baoyun Peng China
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Yun Wu China
Dong Yin China
Yiqiao Mao relative to Jaeyoon Yoo South Korea Jaeyoon Yoo's profile →
Citations per field
00.5×1.5×2.4×
Jaeyoon Yoo · 1×
Citations per year

Countries citing papers authored by Yiqiao Mao

Since Specialization
Citations

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

Fields of papers citing papers by Yiqiao Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yiqiao Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Yiqiao Mao. A scholar is included among the top collaborators of Yiqiao Mao 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 Yiqiao Mao. Yiqiao Mao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
#WorkIndexed citations
1 0
2 0
3 3
4 1
5 4
6 0
7 0
8 2
9 0
10 16
11 2
12 10
13 5
14 42
15
Deep multi-view learning methods: A reviewbreakdown →
199
16 10

About Yiqiao Mao

Yiqiao Mao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Urban Studies, having authored 16 papers that have together received 294 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (7 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Video Analysis and Summarization (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (152 citations), Computational Mathematics (3 citations) and Artificial Intelligence (155 citations). Yiqiao Mao has collaborated with scholars based in China, United Kingdom and Macao. Frequent co-authors include Xiaoqiang Yan, Yangdong Ye, Hui Yu, Shizhe Hu, Mingyuan Li, Xuguang Zhang, Fei‐Yue Wang, Xue Li, Liyuan Zhang and Shaohua Hu. Their work appears in journals such as IEEE Access, Pattern Recognition and Information Sciences.

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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