Fengmao Lv

1.7k citations
58 papers · 1.0k indexed · h-index 17
Topics
Domain Adaptation and Few-Shot Learning (13 papers)Multimodal Machine Learning Applications (8 papers)Advanced Neural Network Applications (5 papers)

In The Last Decade

Fengmao Lv

51 papers receiving 1.0k citations

Peers

Fengmao Lv
Comparison fields: 5 of 103
  • Artificial Intelligence 678
  • Computer Vision and Pattern Recognition 460
  • Signal Processing 100
  • Radiology, Nuclear Medicine and Imaging 95
  • Computer Networks and Communications 87
Replace Changsheng Li with:
Changsheng Li China
Ali Thabet Saudi Arabia
Manosij Ghosh India
Xiaoshan Yang China
Yunhui Guo United States
Manar Ahmed Hamza Saudi Arabia
Haoxuan You United States
Boonserm Kijsirikul Thailand
Yirui Wu China
Quan Cui China
Fengmao Lv relative to Changsheng Li China Changsheng Li's profile →
Citations per field
00.5×1.5×
Changsheng Li · 1×
Citations per year

Countries citing papers authored by Fengmao Lv

Since Specialization
Citations

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

Fields of papers citing papers by Fengmao Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fengmao Lv

This figure shows the co-authorship network connecting the top 25 collaborators of Fengmao Lv. A scholar is included among the top collaborators of Fengmao Lv 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 Fengmao Lv. Fengmao Lv 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
#WorkIndexed citations
1 0
2 0
3 4
4 2
5 0
6 6
7 4
8 4
9 9
10 1
11 4
12 7
13 0
14 0
15 24
16 53
17 29
18 57
19 76
20 12

About Fengmao Lv

Fengmao Lv is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 58 papers that have together received 1.0k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (13 papers), Multimodal Machine Learning Applications (8 papers) and Advanced Neural Network Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (460 citations), Artificial Intelligence (678 citations) and Signal Processing (100 citations). Fengmao Lv has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Lixin Duan, Guosheng Lin, Qing Lian, Boqing Gong, Guowu Yang, Yanyong Huang, Lei Feng, Wenyong Wang, Xiang Chen and Meng Wang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Geophysical Research Letters and Environmental Pollution.

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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