Feras Dayoub
Impact in
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- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Aerospace Engineering top 1%
- Robotics and Sensor-Based Localization
Papers in
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- Advanced Image and Video Retrieval Techniques 25
- Advanced Neural Network Applications 15
- Robotic Path Planning Algorithms 13
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- Robotics and Sensor-Based Localization 30
- Co-authors
- Niko Sünderhauf (23 shared papers)Ben Upcroft (14 shared papers)Chris McCool (9 shared papers)Haoyang Zhang (3 shared papers)Ying Wang (1 shared paper)Tristán Pérez (7 shared papers)Michael John Milford (9 shared papers)Inkyu Sa (3 shared papers)
- Journals
- IEEE Robotics and Automation Letters (4 papers)IEEE Access (3 papers)Computers and Electronics in Agriculture (1 paper)Nature Machine Intelligence (1 paper)Springer tracts in advanced robotics (1 paper)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
Feras Dayoub
67 papers receiving 3.6k citations
Feras Dayoub's Hit Papers
Peers
Comparison fields: 5 of 137
- Computer Vision and Pattern Recognition 1.8k
- Aerospace Engineering 1.2k
- Analytical Chemistry 377
- Plant Science 1.2k
- Industrial and Manufacturing Engineering 224
Countries citing papers authored by Feras Dayoub
This map shows the geographic impact of Feras Dayoub'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 Feras Dayoub with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feras Dayoub more than expected).
Fields of papers citing papers by Feras Dayoub
This network shows the impact of papers produced by Feras Dayoub. 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 Feras Dayoub. The network helps show where Feras Dayoub may publish in the future.
Co-authors
The 25 scholars most cited alongside Feras Dayoub, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | DeepFruits: A Fruit Detection System Using Deep Neural Networks Hit paper breakdown → | 2016 | 899 |
| 2 | VarifocalNet: An IoU-aware Dense Object Detector Hit paper breakdown → | 2021 | 823 |
| 3 | On the performance of ConvNet features for place recognition Hit paper breakdown → | 2015 | 418 |
| 4 | 2015 | 293 | |
| 5 | 2017 | 162 | |
| 6 | 2016 | 118 | |
| 7 | 2021 | 108 | |
| 8 | 2015 | 107 | |
| 9 | 2017 | 103 | |
| 10 | 2020 | 80 | |
| 11 | 2008 | 69 | |
| 12 | 2016 | 67 | |
| 13 | 2021 | 44 | |
| 14 | 2017 | 33 | |
| 15 | 2020 | 32 | |
| 16 | 2015 | 27 | |
| 17 | 2021 | 24 | |
| 18 | 2023 | 24 | |
| 19 | 2019 | 22 | |
| 20 | 2015 | 20 |
About Feras Dayoub
Feras Dayoub is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Artificial Intelligence, Control and Systems Engineering and Plant Science, having authored 76 papers that have together received 3.7k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (30 papers), Advanced Image and Video Retrieval Techniques (25 papers), Advanced Neural Network Applications (15 papers), Robotic Path Planning Algorithms (13 papers), Domain Adaptation and Few-Shot Learning (11 papers), Adversarial Robustness in Machine Learning (9 papers), Smart Agriculture and AI (9 papers) and Robotics and Automated Systems (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.8k citations), Aerospace Engineering (1.2k citations), Analytical Chemistry (377 citations), Plant Science (1.2k citations) and Industrial and Manufacturing Engineering (224 citations). Feras Dayoub has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Niko Sünderhauf, Ben Upcroft, Chris McCool, Haoyang Zhang, Ying Wang, Tristán Pérez, Michael John Milford, Inkyu Sa, Zongyuan Ge and Sareh Abolahrari Shirazi. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Access, Computers and Electronics in Agriculture, Nature Machine Intelligence and Springer tracts in advanced robotics.
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.