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  • Open Access

    ARTICLE

    Investigation on the Chinese Text Sentiment Analysis Based on Convolutional Neural Networks in Deep Learning

    Feng Xu1, Xuefen Zhang2,*, Zhanhong Xin1, Alan Yang3

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 697-709, 2019, DOI:10.32604/cmc.2019.05375

    Abstract Nowadays, the amount of wed data is increasing at a rapid speed, which presents a serious challenge to the web monitoring. Text sentiment analysis, an important research topic in the area of natural language processing, is a crucial task in the web monitoring area. The accuracy of traditional text sentiment analysis methods might be degraded in dealing with mass data. Deep learning is a hot research topic of the artificial intelligence in the recent years. By now, several research groups have studied the sentiment analysis of English texts using deep learning methods. In contrary, relatively few works have so far… More >

  • Open Access

    ARTICLE

    Detecting Iris Liveness with Batch Normalized Convolutional Neural Network

    Min Long1,2,*, Yan Zeng1

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 493-504, 2019, DOI:10.32604/cmc.2019.04378

    Abstract Aim to countermeasure the presentation attack for iris recognition system, an iris liveness detection scheme based on batch normalized convolutional neural network (BNCNN) is proposed to improve the reliability of the iris authentication system. The BNCNN architecture with eighteen layers is constructed to detect the genuine iris and fake iris, including convolutional layer, batch-normalized (BN) layer, Relu layer, pooling layer and full connected layer. The iris image is first preprocessed by iris segmentation and is normalized to 256×256 pixels, and then the iris features are extracted by BNCNN. With these features, the genuine iris and fake iris are determined by… More >

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