The Road to Safety: A Review of Uncertainty and Applications to Autonomous Driving Perception.
B Araújo, JF Teixeira, J Fonseca, R Cerqueira… - …, 2024 - search.ebscohost.com
Deep learning approaches have been gaining importance in several applications. However,
the widespread use of these methods in safety-critical domains, such as Autonomous …
the widespread use of these methods in safety-critical domains, such as Autonomous …
Attacking the out-of-domain problem of a parasite egg detection in-the-wild
N Penpong, Y Wanna, C Kamjanlard, A Techasen… - Heliyon, 2024 - cell.com
The out-of-domain (OO-Do) problem has hindered machine learning models especially
when the models are deployed in the real world. The OO-Do problem occurs during …
when the models are deployed in the real world. The OO-Do problem occurs during …
Long Range Object-Level Monocular Depth Estimation for UAVs
Computer vision-based object detection is a key modality for advanced Detect-And-Avoid
systems that allow for autonomous flight missions of UAVs. While standard object detection …
systems that allow for autonomous flight missions of UAVs. While standard object detection …
Combining pre-trained Vision Transformers and CIDER for Out Of Domain Detection
Out-of-domain (OOD) detection is a crucial component in industrial applications as it helps
identify when a model encounters inputs that are outside the training distribution. Most …
identify when a model encounters inputs that are outside the training distribution. Most …