Feras Dayoub

Feras Dayoub's Home Page


drawing I am a Senior Lecturer with the School of Computer Science and the Australian Institute for Machine Learning (AIML) at the University of Adelaide. I am also an Associate Investigator with QUT Centre for Robotics (QCR). I served as a Chief Investigator of the ARC Centre of Excellence for Robotic Vision (concluded in 2020). My research focuses on enabling the reliable deployment of computer vision and machine learning on mobile robots in real-world environments. I have extensive experience in applied robotic vision research resulting from my work on exciting projects such as AGRobotic detection of weed in farms using deep learning, vision-enabled autonomous underwater vehicles (AUV) to protect the Great Barrier Reef from Crown-of-Thorns Starfish and vision-based infrastructure inspection using unmanned aerial vehicles (UAV). I’ve also lectured in advanced robotics topics for undergraduates, where I taught Bayesian approaches to robot localisation, mapping, and Simultaneous Localisation and Mapping (SLAM).

Academic Career

Awards and Award Finalist

PhD Supervision

Current supervisions

  1. Out-of-Distribution Detection for Deep Semantic Segmentation
    PhD, Principal Supervisor
  2. Deep Learning for Robotics in Open-World Conditions: Uncertainty and Continual Active Learning
    PhD, Associate Supervisor
  3. Autonomous Vehicles Localization without Detailed Prior Maps
    PhD, Principal Supervisor
  4. Solving Manipulation Tasks With Implicit Neural Representations
    PhD, Associate Supervisor

Completed supervisions (Doctorate)

  1. Epistemic uncertainty estimation for object detection in open-set conditions (2021)
  2. Learning From Limited Annotated Data for Re-Identification Problem (2021)
  3. Performance monitoring of deep learning vision systems during deployment (2022)
  4. A Rapidly Deployable Approach for Automated Visual Weed Classification without Prior Species Knowledge (2018)
  5. Integrating Symbolic Spatial Information in Robot Navigation (2018)


The University of Adelaide



Full and up-to-date list found here

Deepfruits: A fruit detection system using deep neural networks I Sa, Z Ge, F Dayoub, B Upcroft, T Perez, C McCool sensors 16 (8), 1222

On the performance of convnet features for place recognition N Sünderhauf, S Shirazi, F Dayoub, B Upcroft, M Milford 2015 IEEE/RSJ international conference on intelligent robots and systems …

Place recognition with convnet landmarks: Viewpoint-robust, condition-robust, training-free N Sünderhauf, S Shirazi, A Jacobson, F Dayoub, E Pepperell, B Upcroft, … Robotics: Science and Systems XI, 1-10

Place categorization and semantic mapping on a mobile robot N Sünderhauf, F Dayoub, S McMahon, B Talbot, R Schulz, P Corke, … 2016 IEEE international conference on robotics and automation (ICRA), 5729-5736

Evaluation of features for leaf classification in challenging conditions D Hall, C McCool, F Dayoub, N Sunderhauf, B Upcroft IEEE Winter Conference on Applications of Computer Vision (WACV), 797-804

Dropout sampling for robust object detection in open-set conditions D Miller, L Nicholson, F Dayoub, N Sünderhauf IEEE International Conference on Robotics and Automation (ICRA)

An adaptive appearance-based map for long-term topological localization of mobile robots F Dayoub, T Duckett 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems …

Long-term experiments with an adaptive spherical view representation for navigation in changing environments F Dayoub, G Cielniak, T Duckett Robotics and Autonomous Systems 59 (5), 285-295

Peduncle detection of sweet pepper for autonomous crop harvesting—combined color and 3-D information I Sa, C Lehnert, A English, C McCool, F Dayoub, B Upcroft, T Perez IEEE Robotics and Automation Letters 2 (2), 765-772

Robot for weed species plant‐specific management O Bawden, J Kulk, R Russell, C McCool, A English, F Dayoub, C Lehnert, … Journal of Field Robotics

Probabilistic object detection: Definition and evaluation D Hall, F Dayoub, J Skinner, H Zhang, D Miller, P Corke, G Carneiro, … IEEE Winter Conference on Applications of Computer Vision 2020

Visual detection of occluded crop: For automated harvesting C McCool, I Sa, F Dayoub, C Lehnert, T Perez, B Upcroft 2016 IEEE International Conference on Robotics and Automation (ICRA), 2506-2512

Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection D Miller, F Dayoub, M Milford, N Sünderhauf IEEE International Conference on Robotics and Automation (ICRA)

Vision-only autonomous navigation using topometric maps F Dayoub, T Morris, B Upcroft, P Corke IEEE/RSJ International Conference on Intelligent Robots and Systems November …

Varifocalnet: An iou-aware dense object detector H Zhang, Y Wang, F Dayoub, N Sünderhauf Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …

Robotic detection and tracking of Crown-Of-Thorns starfish F Dayoub, M Dunbabin, P Corke IEEE/RSJ International Conference on Intelligent Robots and Systems, Hamburg …

Robot navigation using human cues: A robot navigation system for symbolic goal-directed exploration R Schulz, B Talbot, O Lam, F Dayoub, P Corke, B Upcroft, G Wyeth 2015 IEEE International Conference on Robotics and Automation (ICRA), 1100-1105

Multiple map hypotheses for planning and navigating in non-stationary environments T Morris, F Dayoub, P Corke, G Wyeth, B Upcroft IEEE International Conference on Robotics and Automation (ICRA), 2014 1 …

Find my office: Navigating real space from semantic descriptions B Talbot, O Lam, R Schulz, F Dayoub, B Upcroft, G Wyeth 2016 IEEE International Conference on Robotics and Automation (ICRA), 5782-5787

Semantics for Robotic Mapping, Perception and Interaction: A Survey S Garg, N Sünderhauf, F Dayoub, D Morrison, A Cosgun, G Carneiro, … arXiv preprint arXiv:2101.00443