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A comprehensive survey of data augmentation in visual reinforcement learning
Visual reinforcement learning (RL), which makes decisions directly from high-dimensional
visual inputs, has demonstrated significant potential in various domains. However …
visual inputs, has demonstrated significant potential in various domains. However …
[HTML][HTML] A multi-task fusion strategy-based decision-making and planning method for autonomous driving vehicles
W Liu, Z **ang, H Fang, K Huo, Z Wang - Sensors, 2023 - mdpi.com
The autonomous driving technology based on deep reinforcement learning (DRL) has been
confirmed as one of the most cutting-edge research fields worldwide. The agent is enabled …
confirmed as one of the most cutting-edge research fields worldwide. The agent is enabled …
From past to future: rethinking eligibility traces
In this paper, we introduce a fresh perspective on the challenges of credit assignment and
policy evaluation. First, we delve into the nuances of eligibility traces and explore instances …
policy evaluation. First, we delve into the nuances of eligibility traces and explore instances …
Using mel-spectrograms and 2D-CNNs to detect murmurs in variable length phonocardiograms
MS Knorr, JP Bremer - 2022 Computing in Cardiology (CinC), 2022 - ieeexplore.ieee.org
As part of the George B. Moody PhysioNet Challenge 2022, we developed a computational
approach for identifying abnormal cardiac valve function from phonocardiograms (PCGs) …
approach for identifying abnormal cardiac valve function from phonocardiograms (PCGs) …