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In this paper, we put forward deep neural network ensemble to model and predict Chinese stock market index (including Shanghai composite index and SZSE component index), based on the input indices of recent days. A set of component networks are trained by historical data for this task, where Backpropagation and Adam algorithm are used to train each network efficiently. Bagging approach combines these...
In this paper, a novel spatial error concealment (EC) algorithm is proposed. Under the sequential recovery framework, pixels in missing blocks are successively reconstructed based on adaptive linear predictor. The predictor automatically tunes its order and support shape according to local contexts. The predictor order and support shape are determined using Bayesian information criterion, which is...
In this paper, we propose a novel spatial error concealment algorithm based on adaptive linear predictor. The predictor automatically tunes its order and support shape according to local contexts. The optimal order is determined using Bayesian Index Criterion (BIC). The order-adaptive predictor is able to recover more important features or structures. Simulation results show that compared to the state-of-the-art...
Support vector machine (SVM) has been widely applied in the classification of remotely sensed image. How to reduce support vector number in SVM classifier so as to reduce classification time still an important open problem, especially in the case of mass data. To obtain fast classifier with high accuracy, an active learning schema is proposed in the SVM based image classification. Experimental results...
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