TALESS: TSN with Legacy End-Stations Synchronization
IEEE Open Journal of the Industrial Electronics Society (OJIES)
Automated Mask Generation for Efficient YOLO-based Instance Segmentation in Marine Environments for Fish Detection
International WorkShop on Marine Technologies (MARTECH)
Controlling the expansion of Halimeda Incrassata in the Cabrera Natural Park using robots and photo-mosaics
International Symposium on Monitoring Mediterranean Coastal Areas: problems and measurement techniques
Deep learning for detection and counting of Nephrops norvegicus from underwater videos, ICES Journal of Marine Science
ICES Journal of Marine Science
Exploring deep waters: preliminary findings and design insights from a stereo vision unit deployment
The 11th International Workshop on Marine Technology
YOLOv8-based sea urchin detection in ROS for AUV applications
The 11th International Workshop on Marine Technology
Lanty: A Deep Sea Stereo Vision System
IEEE International Conference on Industrial Technology (ICIT)
Microplankton discrimination in FlowCAM images using Deep Learning
19 th International Conference on Computer Vision, Theory and Applications. Complete List of Authors: Francisco Bonin-Font (SRV), Gorka Buenvaron (IFISC), Mary K. Kane and Idan Tuval (IMEDEA)
Combining Progressive Hierarchical Image Encoding and YOLO to Detect Fish in their Natural Habitat
19th International Conference on Computer Vision Theory and Applications (VISAPP)
Coordination of marine multi robot systems with communication constraints
Applied Ocean Research
Data-driven Exploration of Benthic Environments with Autonomous Underwater Vehicles Featuring Semantic Perception and Adaptive Navigation Intelligence
Ph. D. Thesis
Assessing benthic marine habitats colonised with posidonia oceanica using autonomous marine robots and deep learning: A eurofleets campaign
Estuarine, Coastal and Shelf Science
A Deep Learning Approach to Estimate Halimeda incrassata Invasive Stage in the Mediterranean Sea
Marine Science and Engineering
Introducing Guard Frames to Ensure Schedulability of All TSN Traffic Classes
Proceedings of the IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA 2023)