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In order to improve the accuracy of the fault diagnosis of high voltage circuit breaker, an improved DAG-SVM method which is based on the original DAG-SVM is proposed in this paper. The separating characters of samples are evaluated by the average similar measure which contributes to selecting the proper node and optimizing the topology structure of DAG-SVM. Experimental results show that this method...
Very deep convolutional networks have recently demonstrated impressive classification performance on competitive benchmarks such as the ImageNet or COCO tasks. However, training such deep convolutional networks becomes more difficult. In this paper, we propose a novel deep network structure called cross-layer architecture to make the best use of information learned from all the lower-level layers...
Research of the neural network language model in NLP is reviewed. In this paper, the neural network language models are classified into early shallow language models and deep neural network models based on deep learning. This paper emphatically introduces progress of the deep neural network language models, and summarizes the status of deep neural network research's development. Finally, the existing...
The research teaching plays a important role to improve creative spirit, ability and individuality of students. It has great significance to study connotation and development of the research teaching. The research teaching based on cognitivism, humanism, constructivism and modern study theory is formed inchmeal in the education process by all world educators. It advocates that students are the subject...
In real-world applications, labeled data are often inadequate while unlabeled data are available in large quantities. Many semi-supervised learning (SSL) algorithms are proposed to take advantage of unlabeled data. In this paper we propose a novel wrapper method for semi-supervised learning called graph-based selection wrapper (GSW), which aims to improve an existing classifier in a semi-supervised...
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