Benoit Landry

500 citations
14 papers · 318 · h-index 9

Impact in

Papers in

Benoit Landry

14 papers receiving 312 citations

Peers

Benoit Landry
Comparison fields: 5 of 54
  • Human-Computer Interaction 78
  • Control and Systems Engineering 111
  • Cognitive Neuroscience 71
  • Computer Vision and Pattern Recognition 77
  • Aerospace Engineering 60
Replace Marvin K. Bugeja with:
Marvin K. Bugeja Malta
Christoph Engels Germany
Hang Yin China
Cheng Chi China
Jigang Tong China
Jean‐Dominique Gascuel France
Amir M. Ghalamzan E. United Kingdom
Wang Yuan China
Israel Becerra Mexico
Timothy Patten Austria
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Citations per field
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Citations per year

Countries citing papers authored by Benoit Landry

Since Specialization
Citations

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

Fields of papers citing papers by Benoit Landry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Benoit Landry, 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 Benoit Landry Line = papers co-authored together Benoit Landry links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 201990
2 202166
3 201661
4 202024
5 201423
6 201811
7 201511
8 201810
9 20149
10
SEAGuL: Sample Efficient Adversarially Guided Learning of Value Functions.
20214
11
Robust Motion Planning via Perception-Aware Multiobjective Search on GPUs.
20173
12 20142
13 20192
14 20212

About Benoit Landry

Benoit Landry is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Aerospace Engineering, Ecology and Atomic and Molecular Physics, and Optics, having authored 14 papers that have together received 318 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (5 papers), Guidance and Control Systems (3 papers), Robotics and Sensor-Based Localization (2 papers), Color Science and Applications (2 papers), Adversarial Robustness in Machine Learning (2 papers), Leaf Properties and Growth Measurement (2 papers), Remote Sensing in Agriculture (2 papers) and Fault Detection and Control Systems (2 papers). The work is most often cited by research in Human-Computer Interaction (78 citations), Control and Systems Engineering (111 citations), Cognitive Neuroscience (71 citations), Computer Vision and Pattern Recognition (77 citations) and Aerospace Engineering (60 citations). Benoit Landry has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Marco Pavone, Russ Tedrake, Hongkai Dai, Junrui Yang, Sean Follmer, Robin Deits, Pete Florence, James A. Landay, Parastoo Abtahi and Étienne Belin. Their work appears in journals such as Computers and Electronics in Agriculture, Machine Vision and Applications, Fluctuation and Noise Letters, DSpace@MIT (Massachusetts Institute of Technology) and 2021 21st International Conference on Control, Automation and Systems (ICCAS).

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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