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Evidential active recognition: Intelligent and prudent open-world embodied perception
Active recognition enables robots to intelligently explore novel observations thereby
acquiring more information while circumventing undesired viewing conditions. Recent …
acquiring more information while circumventing undesired viewing conditions. Recent …
Weakly-supervised residual evidential learning for multi-instance uncertainty estimation
Uncertainty estimation (UE), as an effective means of quantifying predictive uncertainty, is
crucial for safe and reliable decision-making, especially in high-risk scenarios. Existing UE …
crucial for safe and reliable decision-making, especially in high-risk scenarios. Existing UE …
Revisiting Essential and Nonessential Settings of Evidential Deep Learning
M Chen, J Gao, C Xu - arxiv preprint arxiv:2410.00393, 2024 - arxiv.org
Evidential Deep Learning (EDL) is an emerging method for uncertainty estimation that
provides reliable predictive uncertainty in a single forward pass, attracting significant …
provides reliable predictive uncertainty in a single forward pass, attracting significant …
Trustworthy Behavior Modeling and Decision Making for Autonomous Driving
R Jiao - 2024 - search.proquest.com
Recent advances in deep learning have significantly propelled the development of
autonomous vehicles. However, these systems face critical challenges in system-level …
autonomous vehicles. However, these systems face critical challenges in system-level …
Active Visual Recognition in Open World
L Fan - 2024 - search.proquest.com
Visual recognition, a core area of computer vision, aims to interpret semantic information
from images and videos. With advancements in deep neural networks and substantial …
from images and videos. With advancements in deep neural networks and substantial …