Dan Levi

2.5k citations
20 papers · 1.6k · 1 hit paper · h-index 13

Impact in

Papers in

Dan Levi

19 papers receiving 1.5k citations

Dan Levi's Hit Papers

Recent progress in road and lane detection: a survey 2012 · 550 citations
5500+4+9Years since publication100200300400500

Peers

Dan Levi
Comparison fields: 5 of 82
  • Automotive Engineering 718
  • Computer Vision and Pattern Recognition 1.1k
  • Human-Computer Interaction 154
  • Environmental Engineering 239
  • Media Technology 82
Replace J.C. McCall with:
J.C. McCall United States
Cristiano Premebida Portugal
Patsorn Sangkloy United States
Ho Gi Jung South Korea
Eam Khwang Teoh Singapore
Hangen He China
Xinyu Zhang China
Radu Dănescu Romania
T. Graf Germany
Sayanan Sivaraman United States
Dan Levi relative to J.C. McCall United States J.C. McCall's profile →
Citations per field
00.5×10×
J.C. McCall · 1×
Citations per year

Countries citing papers authored by Dan Levi

Since Specialization
Citations

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

Fields of papers citing papers by Dan Levi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Dan Levi, 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 Dan Levi Line = papers co-authored together Dan Levi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
Recent progress in road and lane detection: a survey
Hit paper breakdown →
2012550
2 2015243
3 2012205
4 2014133
5 2019130
6 201595
7 202278
8 201745
9 201335
10 201424
11 200815
12 201513
13 201112
14 20127
15 20167
16 20185
17 20094
18 20063
19 20152
20 20230

About Dan Levi

Dan Levi is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Artificial Intelligence, Aerospace Engineering and Human-Computer Interaction, having authored 20 papers that have together received 1.6k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (8 papers), Advanced Neural Network Applications (7 papers), Autonomous Vehicle Technology and Safety (5 papers), Advanced Vision and Imaging (5 papers), Machine Learning and Data Classification (4 papers), Robotics and Sensor-Based Localization (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Image and Object Detection Techniques (3 papers). The work is most often cited by research in Automotive Engineering (718 citations), Computer Vision and Pattern Recognition (1.1k citations), Human-Computer Interaction (154 citations), Environmental Engineering (239 citations) and Media Technology (82 citations). Dan Levi has collaborated with scholars based in Israel and United States. Frequent co-authors include Aharon Bar-Hillel, Shaul Oron, Shai Avidan, Noa Garnett, Ethan Fetaya, Wende Zhang, Zehua Huang, Francisco Vicente, Xuehan Xiong and Fernando De la Torre. Their work appears in journals such as Sensors, Machine Vision and Applications, Image and Vision Computing, IEEE Transactions on Intelligent Transportation Systems and International Journal of Computer Vision.

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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