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Future Predictive Success-or-Failure Classification for Long-Horizon Robotic Tasks
The key idea behind the proposed method is an end-to-end approach for determining whether the action plan can complete a given task instead of manually redesigning the conditions.
Non-iterative optimization of pseudo-labeling thresholds for training object detection models from multiple datasets
A popular approach to this problem is first to train teacher models and then to use their confident predictions as pseudo ground-truth labels when training a student model.
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