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Based on chaotic characteristic of high frequency ground-wave radar (HFGWR) sea clutter, a new adaptive artificial neural networks ensemble method for sea clutter predicting is presented in this paper. In phase space reconstructed, when one sea clutter sample is to be predicted, some artificial neural networks are choosed adaptively by evaluating their performance and error correlation in neighborhood...
Location and tracking the human faces is one of the critical technologies in free stereoscopic display system. But because of illumination variation or facial expression, it is difficult to detect human faces accurately and fast. In this paper, an infrared face detection based on real Adaboost algorithm and Cascade structure is implemented. With active infrared illumination, the problem caused by...
Content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap. Hence, relevance feedback has been adopted as a promising approach to improve the search performance. In this paper, we propose a novel idea of learning with historical relevance feedback log-data, and adopt a new methodology called "Collaborative...
This paper gives a deep investigation into AdaBoost algorithm, which is used to boost the performance of any given learning algorithm. Within AdaBoost, weak learners are crucial and primitive parts of the algorithm. Since weak learners are required to train with weights, two types of weak learners: artificial neural network weak learner and naive Bayes weak learner are designed. The results show AdaBoost...
In order to improve the application effect of the collaborative navigation control, this paper presents a Q-learning algorithm based on the path restriction by constructing the absolute distance between a mobile agent of the virtual environment and its destination into a status function of reinforcement learning. In comparison with late and former statuses, a shortest path usually can be achieved...
Neural network and genetic algorithm have attracted a great deal of attention as methods and theories realizing artificial intelligence recently. The combination of these two is drawing more and more attention. This paper demonstrates the possibility of combining neural network with genetic algorithm. An improved genetic algorithm for the learning of neural network's connection weights is presented...
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