Yunqiu Lv

1.1k citations
9 papers · 569 indexed · 2 hit papers · h-index 7
Topics
Visual Attention and Saliency Detection (5 papers)Image Enhancement Techniques (3 papers)Advanced Neural Network Applications (3 papers)

In The Last Decade

Yunqiu Lv

9 papers receiving 558 citations

Hit Papers

Simultaneously Localize, Segment and Rank the Camouflaged...20212026202220242021202150100150200250

Peers

Yunqiu Lv
Comparison fields: 5 of 49
  • Computer Vision and Pattern Recognition 506
  • Sensory Systems 71
  • Aerospace Engineering 56
  • Artificial Intelligence 41
  • Media Technology 40
Replace Qiang Zhai with:
Qiang Zhai China
Mingcan Ma China
Mingchen Zhuge China
Lv Tang China
Hae Jong Seo United States
Guibiao Liao China
David Tsai United States
Yunzhi Zhuge China
Yunqiu Lv relative to Qiang Zhai China Qiang Zhai's profile →
Citations per field
00.5×
Qiang Zhai · 1×
Citations per year

Countries citing papers authored by Yunqiu Lv

Since Specialization
Citations

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

Fields of papers citing papers by Yunqiu Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yunqiu Lv

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

All Works

9 of 9 papers shown
#WorkIndexed citations
1 2
2 13
3 7
4 58
5
Simultaneously Localize, Segment and Rank the Camouflaged Objectsbreakdown →
270
6 22
7
Uncertainty-aware Joint Salient Object and Camouflaged Object Detectionbreakdown →
178
8 16
9 3

About Yunqiu Lv

Yunqiu Lv is a scholar working on Computer Vision and Pattern Recognition, Sensory Systems and Safety, Risk, Reliability and Quality, having authored 9 papers that have together received 569 indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (5 papers), Image Enhancement Techniques (3 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (506 citations), Sensory Systems (71 citations) and Media Technology (40 citations). Yunqiu Lv has collaborated with scholars based in China, Australia and Switzerland. Frequent co-authors include Yuchao Dai, Aixuan Li, Nick Barnes, Deng-Ping Fan, Jing Zhang, Bowen Liu, Tong Zhang, Jing Zhang, Jing Zhang and Jing Zhang. Their work appears in journals such as Scientific Reports, IEEE Transactions on Image Processing and Pattern Recognition.

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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