Feras Dayoub

4.9k citations

55 papers · 3.1k indexed · 3 hit papers · h-index 18

Impact in

Computer Vision and Pattern Recognition top 0.5%
- 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

Computer Vision and Pattern Recognition 37
- Advanced Image and Video Retrieval Techniques 20
- Robotic Path Planning Algorithms 11
- Advanced Neural Network Applications 9
Aerospace Engineering 24
- Robotics and Sensor-Based Localization 24

Co-authors: Niko Sünderhauf Ben Upcroft Chris McCool Tristán Pérez Haoyang Zhang Ying Wang Inkyu Sa Michael Milford
Journals: IEEE Robotics and Automation Letters (3 papers)IEEE Access (2 papers)Journal of Field Robotics (1 paper)Robotics and Autonomous Systems (1 paper)Computers and Electronics in Agriculture (1 paper)
Partner nations: Australia United Kingdom Czechia

In The Last Decade

Feras Dayoub

50 papers receiving 3.0k citations

Hit Papers

align trajectories log scale

VarifocalNet: An IoU-aware Dense Object Detector 2021 · 671 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2021 VarifocalNet: An IoU-aware Dense Object Detector
2016 Sensors
2015 QUT ePrints (Queensland University of Technology)

Peers

Countries citing papers authored by Feras Dayoub

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Feras Dayoub Line = papers co-authored together Feras Dayoub links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	SmartWay: Enhanced Waypoint Prediction and Backtracking for Zero-Shot Vision-and-Language Navigation D. Zhang, Zerui Li, Y Kimura, Jingjing Xia, Feras Dayoub, Miyako W. Wilson, Erin K. Parker	2025	0
2	3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer Jiajun Deng, Tianyu He, Li Jiang, Qwhuqdwlrqdo hswhpehu, Feras Dayoub, 貴美子笠原	2025	0
3	Segment beyond View: Handling Partially Missing Modality for Audio-Visual Semantic Segmentation Proceedings of the AAAI Conference on Artificial Intelligence ·Soney Basnyat, Hu Wang, Feras Dayoub, Hsiang‐Ting Chen	2024	3
4	Hybrid Navigation Acceptability and Safety Proceedings of the AAAI Symposium Series ·Benoı̂t Clément, G. M. Masoud, Paulo E. Santos, Karl Sammut, 実堀切, Feras Dayoub	2024	2
5	Robust Perspective-n-Crater for Crater-based Camera Pose Estimation Хицкова Алина Олеговна, Marta Brtníková, G Daly, Yuta Shimizu, Ryodo Hemmi, Binghong Yang, 藤井英紀, Feras Dayoub, Hideaki Miyamoto, Yukihiro Takahashi, Yasuko Kasai, 罗国梁	2024	0
6	FSNet: A Failure Detection Framework for Semantic Segmentation IEEE Robotics and Automation Letters ·Julianna Magalhães de Almeida, Niko Sünderhauf, Peter Corke, Feras Dayoub	2022	14
7	BenchBot environments for active robotics (BEAR): Simulated data for active scene understanding research The International Journal of Robotics Research ·David Hall, 秦沛, Mutazz Obeid Al Khaldi, 光夫瀧, Joanna Nelle, Feras Dayoub, Niko Sünderhauf	2022	3
8	Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends IEEE Access ·Julianna Magalhães de Almeida, Peter Corke, Feras Dayoub	2021	34
9	VarifocalNet: An IoU-aware Dense Object Detector Haoyang Zhang, Ying Wang, Feras Dayoub, Niko Sünderhauf Hit paper breakdown →	2021	671
10	Benchmarking Sampling-based Probabilistic Object Detectors. QUT ePrints (Queensland University of Technology) ·好章木川, Niko Suenderhauf, Haoyang Zhang, David Hall, Feras Dayoub	2019	12
11	Probability-based Detection Quality (PDQ): A Probabilistic Approach to Detection Evaluation. arXiv (Cornell University) ·David Hall, Feras Dayoub, 暁伊勢川, Peter Corke, Gustavo Carneiro, Niko Sünderhauf	2018	5
12	Combining learning from demonstration and search algorithm for dynamic goal-directed assembly task planning QUT ePrints (Queensland University of Technology) ·Jamie L. Phipps Johnson, Frédéric Maire, Feras Dayoub, Мансуров Э.И.	2018	2
13	Automated topometric graph generation from floor plan analysis QUT ePrints (Queensland University of Technology) ·McMahon Cailin, Feras Dayoub, Ruth Schulz, Peter Corke	2015	3
14	Evaluation of Features for Leaf Classification in Challenging Conditions David Hall, Chris McCool, Feras Dayoub, Niko Sünderhauf, Ben Upcroft	2015	90
15	Text recognition approaches for indoor robotics: a comparison QUT ePrints (Queensland University of Technology) ·McMahon Cailin, Feras Dayoub, Ruth Schulz, Peter Corke	2014	5
16	One Robot, Eight Hours, and Twenty Four Thousand People QUT ePrints (Queensland University of Technology) ·Feras Dayoub, Shi-Long Sun, Ben Upcroft, Peter Corke	2013	1
17	A Sparse Hybrid Map for Vision-Guided Mobile Robots. QUT ePrints (Queensland University of Technology) ·Feras Dayoub, Grzegorz Cielniak, Tom Duckett	2011	4
18	Toward an object-based semantic memory for long-term operation of mobile service robots QUT ePrints (Queensland University of Technology) ·Feras Dayoub, Tom Duckett, Grzegorz Cielniak	2010	5
19	Short- and long-term adaptation of visual place memories for mobile robots QUT ePrints (Queensland University of Technology) ·Feras Dayoub, Tom Duckett, Grzegorz Cielniak	2010	1
20	An adaptive spherical view representation for navigation in changing environments QUT ePrints (Queensland University of Technology) ·Feras Dayoub, Tom Duckett, Grzegorz Cielniak	2009	2

About Feras Dayoub

Feras Dayoub is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Computer Graphics and Computer-Aided Design, Artificial Intelligence and Control and Systems Engineering, having authored 55 papers that have together received 3.1k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (24 papers), Advanced Image and Video Retrieval Techniques (20 papers), Robotic Path Planning Algorithms (11 papers), Advanced Neural Network Applications (9 papers), Smart Agriculture and AI (8 papers), Adversarial Robustness in Machine Learning (6 papers), Robotics and Automated Systems (6 papers) and Anomaly Detection Techniques and Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Aerospace Engineering (1.0k citations), Analytical Chemistry (346 citations), Plant Science (1.1k citations) and Industrial and Manufacturing Engineering (205 citations). Feras Dayoub has collaborated with scholars based in Australia, United Kingdom and Czechia. Frequent co-authors include Niko Sünderhauf, Ben Upcroft, Chris McCool, Tristán Pérez, Haoyang Zhang, Ying Wang, Inkyu Sa, Michael Milford, Zongyuan Ge and Sareh Shirazi. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Access, Journal of Field Robotics, Robotics and Autonomous Systems and Computers and Electronics in Agriculture.

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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