Milad Ramezani

1.1k citations
27 papers · 725 indexed · h-index 13
Topics
Robotics and Sensor-Based Localization (22 papers)3D Surveying and Cultural Heritage (9 papers)Remote Sensing and LiDAR Applications (9 papers)

In The Last Decade

Milad Ramezani

25 papers receiving 709 citations

Peers

Milad Ramezani
Comparison fields: 5 of 58
  • Aerospace Engineering 489
  • Computer Vision and Pattern Recognition 279
  • Electrical and Electronic Engineering 262
  • Geology 201
  • Environmental Engineering 152
Replace Michael Ruhnke with:
Michael Ruhnke Germany
Denis F. Wolf Brazil
Sören Schwertfeger China
Geoffrey Pascoe United Kingdom
Shenghai Yuan Singapore
Renaud Dubé Switzerland
Johannes Meyer Germany
Naoki Akai Japan
Damien Vivet France
Henning Lategahn Germany
Milad Ramezani relative to Michael Ruhnke Germany Michael Ruhnke's profile →
Citations per field
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Citations per year

Countries citing papers authored by Milad Ramezani

Since Specialization
Citations

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

Fields of papers citing papers by Milad Ramezani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Milad Ramezani

This figure shows the co-authorship network connecting the top 25 collaborators of Milad Ramezani. A scholar is included among the top collaborators of Milad Ramezani 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 Milad Ramezani. Milad Ramezani 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 6
3 2
4 5
5 31
6 2
7 4
8 17
9 59
10 4
11 33
12 5
13 160
14 5
15 69
16 131
17 44
18 15
19 17
20 14

About Milad Ramezani

Milad Ramezani is a scholar working on Geology, Aerospace Engineering and Environmental Engineering, having authored 27 papers that have together received 725 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (22 papers), 3D Surveying and Cultural Heritage (9 papers) and Remote Sensing and LiDAR Applications (9 papers). The work is most often cited by research in Geology (201 citations), Aerospace Engineering (489 citations) and Computer Vision and Pattern Recognition (279 citations). Milad Ramezani has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Kourosh Khoshelham, Debaditya Acharya, Maurice Fallon, Fuqiang Gu, Peyman Moghadam, Sridha Sridharan, Clinton Fookes, Xuke Hu, Shahrokh Valaee and Jianga Shang. Their work appears in journals such as SHILAP Revista de lepidopterología, ACM Computing Surveys and The International Journal of Robotics Research.

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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