Advances of machine learning in materials science: Ideas and techniques
In this big data era, the use of large dataset in conjunction with machine learning (ML) has
been increasingly popular in both industry and academia. In recent times, the field of …
been increasingly popular in both industry and academia. In recent times, the field of …
[HTML][HTML] An ontology-based system to avoid UAS flight conflicts and collisions in dense traffic scenarios
D Martín-Lammerding, JJ Astrain, A Córdoba… - Expert Systems with …, 2023 - Elsevier
Abstract New Unmanned Aerial Systems (UAS) applications will increase air traffic densities
in metropolitan regions. Collision avoidance systems (CAS) are a key component in …
in metropolitan regions. Collision avoidance systems (CAS) are a key component in …
Formal verification of neural networks for safety-critical tasks in deep reinforcement learning
In the last years, neural networks achieved groundbreaking successes in a wide variety of
applications. However, for safety critical tasks, such as robotics and healthcare, it is …
applications. However, for safety critical tasks, such as robotics and healthcare, it is …
[HTML][HTML] Uncovering heterogeneous effects in computational models for sustainable decision-making
Computational modeling is frequently incorporated into environmental decision-making in
order to capture inherently complex relationships and system dynamics. The complexity of …
order to capture inherently complex relationships and system dynamics. The complexity of …
ACAS sXu: Robust decentralized detect and avoid for small unmanned aircraft systems
Demand for small unmanned aircraft systems (sUAS) continues to increase in diversity and
volume, however applications are currently limited by regulatory requirements for visual …
volume, however applications are currently limited by regulatory requirements for visual …
Obstacle avoidance for uas in continuous action space using deep reinforcement learning
Obstacle avoidance for small unmanned aircraft is vital for the safety of future urban air
mobility (UAM) and Unmanned Aircraft System (UAS) Traffic Management (UTM). There are …
mobility (UAM) and Unmanned Aircraft System (UAS) Traffic Management (UTM). There are …
Efficient statistical assessment of neural network corruption robustness
We quantify the robustness of a trained network to input uncertainties with a stochastic
simulation inspired by the field of Statistical Reliability Engineering. The robustness …
simulation inspired by the field of Statistical Reliability Engineering. The robustness …
AVOIDDS: aircraft vision-based intruder detection dataset and simulator
Designing robust machine learning systems remains an open problem, and there is a need
for benchmark problems that cover both environmental changes and evaluation on a …
for benchmark problems that cover both environmental changes and evaluation on a …
Integrated conflict management for uam with strategic demand capacity balancing and learning-based tactical deconfliction
Urban air mobility (UAM) has the potential to revolutionize our daily transportation, offering
rapid and efficient deliveries of passengers and cargo between dedicated locations within …
rapid and efficient deliveries of passengers and cargo between dedicated locations within …
ACETONE: predictable programming framework for ML applications in safety-critical systems
Machine learning applications have been gaining considerable attention in the field of safety-
critical systems. Nonetheless, there is up to now no accepted development process that …
critical systems. Nonetheless, there is up to now no accepted development process that …