Sorin Grigorescu

33 papers receiving 1.2k citations

Hit Papers

A survey of deep learning techniques for autonomous driving201920262021202320192505007501000

Peers

Sorin Grigorescu
Comparison fields: 5 of 123
  • Computer Vision and Pattern Recognition 469
  • Artificial Intelligence 429
  • Automotive Engineering 277
  • Control and Systems Engineering 182
  • Electrical and Electronic Engineering 173
Replace Gigel Măceșanu with:
Gigel Măceșanu Romania
Tiberiu Cocias Romania
Ekim Yurtsever United States
Edward Tunstel United States
Alexander Amini United States
Hongbin Sun China
David Meger Canada
Antonio Loquercio United States
Urs Müller United States
Wilko Schwarting United States
Sorin Grigorescu relative to Gigel Măceșanu Romania Gigel Măceșanu's profile →
Citations per field
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Gigel Măceșanu · 1×
Citations per year

Countries citing papers authored by Sorin Grigorescu

Since Specialization
Citations

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

Fields of papers citing papers by Sorin Grigorescu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sorin Grigorescu

This figure shows the co-authorship network connecting the top 25 collaborators of Sorin Grigorescu. A scholar is included among the top collaborators of Sorin Grigorescu 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 Sorin Grigorescu. Sorin Grigorescu 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
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5 12
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A survey of deep learning techniques for autonomous drivingbreakdown →
1025
7 1
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9 0
10
Time-delay analysis of a robotic stereo active vision system
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11
AN OBJECT DETECTION AND 3D RECONSTRUCTION APPROACH FOR REAL-TIME SCENE UNDERSTANDING
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12
Camera Calibration for Reliable Object Manipulation in Care-Providing Robot FRIEND
3
13 2
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Robust Machine Vision for Service Robotics
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FRIEND - A Dependable Semiautonomous Rehabilitation
3
16 0
17 10
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20 12

About Sorin Grigorescu

Sorin Grigorescu is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Media Technology, having authored 39 papers that have together received 1.3k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (15 papers), Advanced Vision and Imaging (13 papers) and Autonomous Vehicle Technology and Safety (6 papers). The work is most often cited by research in Automotive Engineering (277 citations), Computer Vision and Pattern Recognition (469 citations) and Health Informatics (19 citations). Sorin Grigorescu has collaborated with scholars based in Romania, Germany and United States. Frequent co-authors include Tiberiu Cocias, Gigel Măceșanu, Bogdan Trăsnea, Axel Gräser, Thorsten Lüth, Danijela Ristić–Durrant, Anita Graser, Claudiu Pozna, Dan Puiu and Federico Lombardi. Their work appears in journals such as Sensors, Applied Surface Science and IEEE Transactions on Neural Networks and Learning Systems.

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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