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In this paper, an adaptive state aggregation Q-Learning method, with the capability of multi-agent cooperation, was proposed to enhance the efficiency of reinforcement learning (RL) and applied to box-pushing tasks for humanoid robots. First, a decision tree was applied to partition the state space according to temporary differences in reinforcement learning, so that a real valued action domain could...
Over the past few years, multi-view face detection issue has become one of the most attractive research topics in the field of computer vision. In this paper, a novel automatic system for multi-view face detection and pose estimation is proposed. Our approach adopts modified appearance-based learning methods to build corresponding face detectors and pose estimators, and detects multi-view faces according...
This paper proposes a frontal staircase detection algorithm using both classical Haar-like features and a novel set of PCA-base Haar-like features. Real AdaBoost is used for training a cascaded classifier. The PCA-based Haar-like features are extremely efficient at rejecting background regions at early stages in the cascade. A specifically designed scanning scheme made the algorithm constantly time...
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