7 citations · 17 across the 16 of their papers we have counts for
6 papers · 1 filter
A comprehensive review of datasets and deep learning techniques for vision in Unmanned Surface Vehicles
Linh Trinh, Siegfried Mercelis, Ali Anwar
Unmanned Surface Vehicles (USVs) have emerged as a major platform in maritime operations, capable of supporting a wide range of applications. USVs can help reduce labor costs, incr…
Evaluating Robustness of Reinforcement Learning Algorithms for Autonomous Shipping
Bavo Lesy, Ali Anwar, Siegfried Mercelis
Recently, there has been growing interest in autonomous shipping due to its potential to improve maritime efficiency and safety. The use of advanced technologies, such as artificia…
Improving classification of road surface conditions via road area extraction and contrastive learning
Linh Trinh, Ali Anwar, Siegfried Mercelis
Maintaining roads is crucial to economic growth and citizen well-being because roads are a vital means of transportation. In various countries, the inspection of road surfaces is s…
Multiple data sources and domain generalization learning method for road surface defect classification
Linh Trinh, Ali Anwar, Siegfried Mercelis
Roads are an essential mode of transportation, and maintaining them is critical to economic growth and citizen well-being. With the continued advancement of AI, road surface inspec…
Data selection method for assessment of autonomous vehicles
Linh Trinh, Ali Anwar, Siegfried Mercelis
As the popularity of autonomous vehicles has grown, many standards and regulators, such as ISO, NHTSA, and Euro NCAP, require safety validation to ensure a sufficient level of safe…
Robust Model-Based Reinforcement Learning with an Adversarial Auxiliary Model
Siemen Herremans, Ali Anwar, Siegfried Mercelis
Reinforcement learning has demonstrated impressive performance in various challenging problems such as robotics, board games, and classical arcade games. However, its real-world ap…