Tag: Active Learning
All the articles with the tag "Active Learning".
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Label-efficient Single Photon Images Classification via Active Learning
This paper proposes an active learning framework for single-photon image classification that uses imaging condition-aware synthetic augmentation and a diversity-guided uncertainty-inconsistency sampling strategy to achieve high accuracy (97% on synthetic, 90.63% on real-world data) with significantly fewer labeled samples (1.5% and 8%, respectively) compared to baselines.
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Learning to Drift in Extreme Turning with Active Exploration and Gaussian Process Based MPC
This paper introduces AEDGPR-MPC, a framework combining Model Predictive Control with Gaussian Process Regression and active exploration to correct vehicle model mismatches, achieving significant reductions in lateral error (up to 52.8% in simulation, 36.7% in RC car tests) and velocity tracking RMSE during extreme cornering drift control.