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Found 5 papers, 2 papers with code
A Fully Data-Driven Approach for Realistic Traffic Signal Control Using Offline Reinforcement Learning
Specifically, we combine well-established traffic flow theory with machine learning to construct a reward inference model to infer the reward signals from coarse-grained traffic data.
Progression-Guided Temporal Action Detection in Videos
The framework locates actions in videos by detecting the action evolution process.
TraffNet: Learning Causality of Traffic Generation for What-if Prediction
Real-time what-if traffic prediction is crucial for decision making in intelligent traffic management and control.
Serial-parallel Multi-Scale Feature Fusion for Anatomy-Oriented Hand Joint Detection
Accurate hand joints detection from images is a fundamental topic which is essential for many applications in computer vision and human computer interaction.
A Dynamic Model for Traffic Flow Prediction Using Improved DRN
In our research, we improve the Deep Residual Network and build a dynamic model which previous researchers hardly use.
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