L. Minh Dang

3.6k citations
71 papers · 2.5k indexed · 2 hit papers · h-index 24
Topics
Smart Agriculture and AI (17 papers)Infrastructure Maintenance and Monitoring (13 papers)Water Systems and Optimization (10 papers)
Journals
SHILAP Revista de lepidopterologíaScientific ReportsConstruction and Building Materials
Partner nations
South KoreaVietnamChina

In The Last Decade

L. Minh Dang

64 papers receiving 2.4k citations

Hit Papers

Sensor-based and vision-based human activity recognition:...201920262021202320202019100200300400

Peers

L. Minh Dang
Comparison fields: 5 of 142
  • Computer Vision and Pattern Recognition 830
  • Civil and Structural Engineering 532
  • Computer Networks and Communications 357
  • Plant Science 326
  • Artificial Intelligence 315
Replace Hyeonjoon Moon with:
Hyeonjoon Moon South Korea
Joon Huang Chuah Malaysia
Muhammad Shoaib Pakistan
Saiedeh Razavi Canada
Chao Huang China
Paolo Barsocchi Italy
Angelos Amditis Greece
Alaa Khamis Canada
Argel A. Bandala Philippines
Gabriel Villarrubia González Spain
L. Minh Dang relative to Hyeonjoon Moon South Korea Hyeonjoon Moon's profile →
Citations per field
00.5×1.5×
Hyeonjoon Moon · 1×
Citations per year

Countries citing papers authored by L. Minh Dang

Since Specialization
Citations

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

Fields of papers citing papers by L. Minh Dang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by L. Minh Dang. 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 L. Minh Dang. The network helps show where L. Minh Dang may publish in the future.

Co-authorship network of co-authors of L. Minh Dang

This figure shows the co-authorship network connecting the top 25 collaborators of L. Minh Dang. A scholar is included among the top collaborators of L. Minh Dang 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 L. Minh Dang. L. Minh Dang 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 1
3 0
4 0
5 5
6 4
7 1
8 9
9 0
10 11
11 6
12 10
13 22
14 5
15 10
16 13
17 29
18 12
19 27
20 95

About L. Minh Dang

L. Minh Dang is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Civil and Structural Engineering, having authored 71 papers that have together received 2.5k indexed citations. Recurring topics across this work include Smart Agriculture and AI (17 papers), Infrastructure Maintenance and Monitoring (13 papers) and Water Systems and Optimization (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (830 citations), Civil and Structural Engineering (532 citations) and Computer Networks and Communications (357 citations). L. Minh Dang has collaborated with scholars based in South Korea, Vietnam and China. Frequent co-authors include Hyeonjoon Moon, Hanxiang Wang, Md. Jalil Piran, Kyungbok Min, Yanfen Li, Hyeonjoon Moon, Dongil Han, Tan N. Nguyen, Syed Ibrahim Hassan and Hyoung‐Kyu Song. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Construction and Building Materials.

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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