Ehsan Asadi

31 papers receiving 783 citations

Ehsan Asadi's Hit Papers

3D point cloud data processing with machine learning for construction and infrastructure applications: A comprehensive review 2021 · 162 citations
1620+1+3Years since publication50100150

Peers

Ehsan Asadi
Comparison fields: 5 of 57
  • Geology 107
  • Building and Construction 146
  • Control and Systems Engineering 224
  • Computer Vision and Pattern Recognition 137
  • Aerospace Engineering 99
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He Xie China
Wei Guan China
Gavin Paul Australia
Santiago Martínez Spain
Juan G. Victores Spain
Jacek Wodecki Poland
Siyun Chen China
Fernando Moreu United States
In‐Ho Kim South Korea
Ehsan Asadi relative to He Xie China He Xie's profile →
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Countries citing papers authored by Ehsan Asadi

Since Specialization
Citations

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

Fields of papers citing papers by Ehsan Asadi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1
3D point cloud data processing with machine learning for construction and infrastructure applications: A comprehensive review
Hit paper breakdown →
2021162
2 201897
3 201795
4 202366
5 201945
6 201844
7 202341
8 200931
9 202123
10 201820
11 202220
12 201819
13 202216
14 202315
15 202514
16 201813
17 201411
18 201611
19 202411
20 20229

About Ehsan Asadi

Ehsan Asadi is a scholar working on Control and Systems Engineering, Geology, Aerospace Engineering, Computer Vision and Pattern Recognition and Building and Construction, having authored 35 papers that have together received 803 indexed citations. Recurring topics across this work include Inertial Sensor and Navigation (6 papers), Robotics and Sensor-Based Localization (5 papers), 3D Surveying and Cultural Heritage (5 papers), Robotic Mechanisms and Dynamics (5 papers), Robot Manipulation and Learning (5 papers), Advanced Neural Network Applications (4 papers), BIM and Construction Integration (3 papers) and Target Tracking and Data Fusion in Sensor Networks (2 papers). The work is most often cited by research in Geology (107 citations), Building and Construction (146 citations), Control and Systems Engineering (224 citations), Computer Vision and Pattern Recognition (137 citations) and Aerospace Engineering (99 citations). Ehsan Asadi has collaborated with scholars based in Australia, Singapore and United Kingdom. Frequent co-authors include I-Ming Chen, Mehrdad Arashpour, Kaveh Mirzaei, Hossein Masoumi, Huixu Dong, Bingbing Forrest Li, Ali Behnood, Yu Bai, Jian S. Dai and Chen Qiu. Their work appears in journals such as Robotics and Computer-Integrated Manufacturing, Advanced Engineering Informatics, IEEE/ASME Transactions on Mechatronics, Mechanism and Machine Theory and IEEE Transactions on Intelligent Vehicles.

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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