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The models based on deep convolutional networks and recurrent neural networks have dominated in recent image caption generation tasks. Performance and complexity are still eternal topic. Inspired by recent work, by combining the advantages of simple RNN and LSTM, we present a novel parallel-fusion RNN-LSTM architecture, which obtains better results than a dominated one and improves the efficiency...
The newly proposed video coding standard, High Efficiency Video Coding (HEVC), has been widely accepted and adopted by industry and academia due to its better coding efficiency compared with H.264/AVC. While HEVC achieves an increase of about 40% in coding efficiency, its computational complexity has been increased significantly. Given this, a high performance AVC to HEVC transcoder is needed urgently...
In High Efficiency Video Coding (HEVC), the computational complexity has been increased so that an Early SKIP mode decision method is proposed by using coded block flag of an inter prediction unit (PU) to speed up mode decision with BD-bitrate increase. In this paper, we propose a fast SKIP mode decision algorithm to speed up PU mode decision for HEVC in a rate-distortion (RD) optimization sense....
In order to improve forecasting model accuracy of BP neural network, an improved prediction method of optimized BP neural network based on modified particle swarm optimization algorithm (PSO) was proposed. In this modified PSO algorithm, an adaptive mutation operator was proposed in PSO to change positions of the particles plunged in the local optimization. The modified PSO was used to optimize the...
Abstract--By the research on evaluation index system of entrepreneurial team training mode, we carry on the direct analysis of reasonableness of training mode, so that it can promote the development of entrepreneurial team training mode and improve the competitiveness of the organization. This paper starts at domestic and foreign research status, and analyzes the dynamic mechanism of entrepreneurial...
Aiming at the disadvantages of prediction model of single BP neural network, a prediction model was presented by combining AdaBoost algorithm and BP neural network for improving the forecasting accuracy of single BP neural network. A new updating method is proposed for the characters of ensemble BP neural network based on AdaBoost. The new method can update the model effectively and overcome the disadvantage...
In order to improve the correct rate of transformer fault diagnosis based on three-ratio method of traditional dissolved gas analysis (DGA), a novel intelligent transformer fault diagnosis method based on both DGA and probabilistic neural network (PNN) was proposed. In this fault diagnosis method, it takes three characteristic values of the improved three-ratio method as its inputs and five transformer...
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