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Deep Reinforcement Learning for Time-Critical Wilderness Search And Rescue Using Drones
This allows the deep reinforcement learning agent to learn optimal flight paths that maximize the probability of finding the missing person quickly.
Interpretable Climate Change Modeling With Progressive Cascade Networks
Typical deep learning approaches to modeling high-dimensional data often result in complex models that do not easily reveal a new understanding of the data.
Finding Temporally Consistent Occlusion Boundaries in Videos using Geometric Context
Our proposed framework provides an efficient approach for finding temporally consistent occlusion boundaries in video by utilizing causality, redundancy in videos, and semantic layout of the scene.
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