Gigel Măceșanu
Impact in
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
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- Advanced Neural Network Applications
- Robotic Path Planning Algorithms
- Video Surveillance and Tracking Methods
Papers in
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- Advanced Vision and Imaging 5
- Robotic Path Planning Algorithms 3
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- Robotics and Sensor-Based Localization 4
- Co-authors
- Sorin Grigorescu (8 shared papers)Tiberiu Cocias (5 shared papers)Bogdan Trăsnea (3 shared papers)Dan Puiu (1 shared paper)Claudiu Pozna (1 shared paper)
- Journals
- Journal of Intelligent & Robotic Systems (1 paper)Sensors (1 paper)Journal of Field Robotics (1 paper)Robotics and Autonomous Systems (1 paper)Advances in intelligent systems and computing (1 paper)
In The Last Decade
Gigel Măceșanu
7 papers receiving 1.2k citations
Gigel Măceșanu's Hit Papers
Peers
Comparison fields: 5 of 117
- Automotive Engineering 292
- Computer Vision and Pattern Recognition 443
- Health Informatics 21
- Artificial Intelligence 479
- Software 36
Countries citing papers authored by Gigel Măceșanu
This map shows the geographic impact of Gigel Măceșanu'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 Gigel Măceșanu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gigel Măceșanu more than expected).
Fields of papers citing papers by Gigel Măceșanu
This network shows the impact of papers produced by Gigel Măceșanu. 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 Gigel Măceșanu. The network helps show where Gigel Măceșanu may publish in the future.
Co-authors
The 5 scholars most cited alongside Gigel Măceșanu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A survey of deep learning techniques for autonomous driving Hit paper breakdown → | 2019 | 1168 |
| 2 | 2011 | 19 | |
| 3 | 2013 | 11 | |
| 4 | 2021 | 7 | |
| 5 | 2010 | 5 | |
| 6 | Time-delay analysis of a robotic stereo active vision system | 2011 | 3 |
| 7 | On the real-time modelling of a robotic scene perception and estimation system | 2011 | 1 |
| 8 | 2025 | 0 | |
| 9 | 2017 | 0 | |
| 10 | 2012 | 0 |
About Gigel Măceșanu
Gigel Măceșanu is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Automotive Engineering, Control and Systems Engineering and Human-Computer Interaction, having authored 10 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (5 papers), Robotics and Sensor-Based Localization (4 papers), Robotic Path Planning Algorithms (3 papers), Autonomous Vehicle Technology and Safety (2 papers), Gaze Tracking and Assistive Technology (2 papers), Control and Dynamics of Mobile Robots (1 paper), Robotic Mechanisms and Dynamics (1 paper) and Human-Automation Interaction and Safety (1 paper). The work is most often cited by research in Automotive Engineering (292 citations), Computer Vision and Pattern Recognition (443 citations), Health Informatics (21 citations), Artificial Intelligence (479 citations) and Software (36 citations). Gigel Măceșanu has collaborated with scholars based in Romania and Germany. Frequent co-authors include Sorin Grigorescu, Tiberiu Cocias, Bogdan Trăsnea, Dan Puiu and Claudiu Pozna. Their work appears in journals such as Journal of Intelligent & Robotic Systems, Sensors, Journal of Field Robotics, Robotics and Autonomous Systems and Advances in intelligent systems and computing.
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.