Jérôme Guzzi

1.6k citations
28 papers · 735 indexed · 1 hit paper · h-index 10

Impact in

Papers in

Jérôme Guzzi

26 papers receiving 702 citations

Hit Papers

A Machine Learning Approach to Visual Perception of Forest Trails for Mobile Robots 2015 · 414 citations
4142015202620182022100200300400

Peers

Jérôme Guzzi
Comparison fields: 5 of 74
  • Computer Vision and Pattern Recognition 433
  • Aerospace Engineering 304
  • Human-Computer Interaction 47
  • Artificial Intelligence 196
  • Control and Systems Engineering 122
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Citations per year

Countries citing papers authored by Jérôme Guzzi

Since Specialization
Citations

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

Fields of papers citing papers by Jérôme Guzzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Jérôme Guzzi, 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 Jérôme Guzzi Line = papers co-authored together Jérôme Guzzi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Machine Learning Approach to Visual Perception of Forest Trails for Mobile Robots
Hit paper breakdown →
2015414
2 201371
3 202243
4 201436
5 202033
6 201428
7 201513
8 202212
9 202210
10 202210
11 20189
12 20208
13 20186
14 20185
15 20135
16 20194
17 20183
18 20233
19 20193
20 20213

About Jérôme Guzzi

Jérôme Guzzi is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Aerospace Engineering, Control and Systems Engineering and Cognitive Neuroscience, having authored 28 papers that have together received 735 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (10 papers), Robotic Path Planning Algorithms (6 papers), Robot Manipulation and Learning (5 papers), Video Surveillance and Tracking Methods (5 papers), Distributed Control Multi-Agent Systems (3 papers), Hand Gesture Recognition Systems (3 papers), UAV Applications and Optimization (3 papers) and Tactile and Sensory Interactions (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (433 citations), Aerospace Engineering (304 citations), Human-Computer Interaction (47 citations), Artificial Intelligence (196 citations) and Control and Systems Engineering (122 citations). Jérôme Guzzi has collaborated with scholars based in Switzerland, Italy and Qatar. Frequent co-authors include Alessandro Giusti, Luca Maria Gambardella, Gianni A. Di, Christian Förster, J. Rodriguez, Flavio Fontana, Matthias Faessler, Davide Scaramuzza, Dan Cireşan and Jürgen Schmidhuber. Their work appears in journals such as IEEE Robotics and Automation Letters, Data in Brief, Autonomous Robots, SHILAP Revista de lepidopterología and Adaptive Agents and Multi-Agents 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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