Ming Lv

22 papers receiving 545 citations

Peers

Ming Lv
Comparison fields: 5 of 65
  • Energy Engineering and Power Technology 50
  • Renewable Energy, Sustainability and the Environment 124
  • Catalysis 46
  • Electronic, Optical and Magnetic Materials 117
  • Media Technology 52
Replace Jun Lee with:
Jun Lee South Korea
Kamilia Aokal United Arab Emirates
Peter Ozaveshe Oviroh South Africa
Emilio Navarro Spain
Gerardo Nicoletti Italy
Myungjun Kim South Korea
Muhammed Ali Malaysia
Saiful Hasmady Abu Hassan Malaysia
Martijn J.J. Mulder Netherlands
S. Elangovan United States
Ming Lv relative to Jun Lee South Korea Jun Lee's profile →
Citations per field
00.5×10×17.3×
Jun Lee · 1×
Citations per year

Countries citing papers authored by Ming Lv

Since Specialization
Citations

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

Fields of papers citing papers by Ming Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011122
2 201475
3 201768
4 202154
5 202136
6 202435
7 202134
8 201328
9 202419
10 202413
11 202310
12 202110
13 20258
14 20247
15 20147
16 20256
17 20076
18 20235
19 20244
20 20242

About Ming Lv

Ming Lv is a scholar working on Media Technology, Materials Chemistry, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Atmospheric Science, having authored 24 papers that have together received 551 indexed citations. Recurring topics across this work include Advanced Image Fusion Techniques (6 papers), Remote-Sensing Image Classification (4 papers), Remote Sensing and Land Use (3 papers), Advanced Image Processing Techniques (3 papers), Advancements in Solid Oxide Fuel Cells (2 papers), Image Enhancement Techniques (2 papers), Advanced Fiber Optic Sensors (2 papers) and Polymer Nanocomposites and Properties (2 papers). The work is most often cited by research in Energy Engineering and Power Technology (50 citations), Renewable Energy, Sustainability and the Environment (124 citations), Catalysis (46 citations), Electronic, Optical and Magnetic Materials (117 citations) and Media Technology (52 citations). Ming Lv has collaborated with scholars based in China, Italy and Malaysia. Frequent co-authors include Yanmei Zhang, Cuixue Chen, Wei Li, Jun Fang, Hongbing Ma, Liangliang Li, Le Wu, Yuqi Wang, Xin Yang and Lan Zheng. Their work appears in journals such as Remote Sensing, Frontiers in Marine Science, Ceramics International, International Journal of Hydrogen Energy and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

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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