Dalton Lunga

52 papers receiving 667 citations

Peers

Dalton Lunga
Comparison fields: 5 of 109
  • Media Technology 298
  • Computer Vision and Pattern Recognition 197
  • Atmospheric Science 160
  • Geography, Planning and Development 38
  • Artificial Intelligence 164
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Kunlun Qi China
Saman Ghaffarian Netherlands
H. Lexie Yang United States
Xiaodao Chen China
Marjan Alirezaie Sweden
Yehua Sheng China
Weijing Song China
Dongyang Hou China
Yakun Xie China
Grant J. Scott United States
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Citations per year

Countries citing papers authored by Dalton Lunga

Since Specialization
Citations

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

Fields of papers citing papers by Dalton Lunga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013222
2 202070
3 201236
4 201934
5 202231
6 201830
7 201928
8 201924
9 202423
10 201717
11 201916
12 202113
13 202113
14 201312
15 201810
16 20188
17 20237
18 20227
19 20197
20 20206

About Dalton Lunga

Dalton Lunga is a scholar working on Media Technology, Geography, Planning and Development, Computer Vision and Pattern Recognition, Ocean Engineering and Artificial Intelligence, having authored 59 papers that have together received 693 indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (26 papers), Advanced Neural Network Applications (11 papers), Geographic Information Systems Studies (10 papers), Domain Adaptation and Few-Shot Learning (8 papers), Geochemistry and Geologic Mapping (8 papers), Automated Road and Building Extraction (8 papers), Remote Sensing and Land Use (7 papers) and Remote Sensing in Agriculture (7 papers). The work is most often cited by research in Media Technology (298 citations), Computer Vision and Pattern Recognition (197 citations), Atmospheric Science (160 citations), Geography, Planning and Development (38 citations) and Artificial Intelligence (164 citations). Dalton Lunga has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Okan K. Ersoy, Saurabh Prasad, Melba M. Crawford, H. Lexie Yang, Budhendra Bhaduri, Jiangye Yuan, Shawn Newsam, Song Gao, Yingjie Hu and Wenwen Li. Their work appears in journals such as IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, IEEE Geoscience and Remote Sensing Magazine, IEEE Geoscience and Remote Sensing Letters and IEEE Signal Processing Magazine.

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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