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  • Open Access


    Visualization for Explanation of Deep Learning-Based Defect Detection Model Using Class Activation Map

    Hyunkyu Shin1, Yonghan Ahn2, Mihwa Song3, Heungbae Gil3, Jungsik Choi4,*, Sanghyo Lee5,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4753-4766, 2023, DOI:10.32604/cmc.2023.038362

    Abstract Recently, convolutional neural network (CNN)-based visual inspection has been developed to detect defects on building surfaces automatically. The CNN model demonstrates remarkable accuracy in image data analysis; however, the predicted results have uncertainty in providing accurate information to users because of the “black box” problem in the deep learning model. Therefore, this study proposes a visual explanation method to overcome the uncertainty limitation of CNN-based defect identification. The visual representative gradient-weights class activation mapping (Grad-CAM) method is adopted to provide visually explainable information. A visualizing evaluation index is proposed to quantitatively analyze visual representations; this index reflects a rough estimate… More >

  • Open Access


    Evaluation Model of Farmer Training Effect Based on AHP–A Case Study of Hainan Province

    Shengjie Li, Chaosheng Tang*

    Journal on Artificial Intelligence, Vol.3, No.2, pp. 55-62, 2021, DOI:10.32604/jai.2021.017408

    Abstract On the basis of studying the influencing factors of training effect evaluation, this paper constructs an AHP-fuzzy comprehensive evaluation model for farmers’ vocational training activities in Hainan Province to evaluate farmers’ training effect, which overcomes the limitations of traditional methods. Firstly, the content and index system of farmer training effect evaluation are established by analytic hierarchy process, and the weight value of each index is determined. Then, the fuzzy comprehensive evaluation (FCE) of farmer training effect is carried out by using multi-level FCE. The joint use of AHP and FCE improves the reliability and effectiveness of the evaluation process and… More >

  • Open Access


    Coverless Text Hiding Method Based on Improved Evaluation Index and One-Bit Embedding

    Ning Wu1,2, Yi Yang1,*, Lian Li1, Zhongliang Yang3, Poli Shang4, Weibo Ma5, Zhenru Liu5

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1035-1048, 2020, DOI:10.32604/cmes.2020.010450

    Abstract In the field of information hiding, text is less redundant, which leads to less space to hide information and challenging work for researchers. Based on the Markov chain model, this paper proposes an improved evaluation index and onebit embedding coverless text steganography method. In the steganography process, this method did not simply take the transition probability as the optimization basis of the steganography model, but combined it with the sentence length in the corresponding nodes in the model to gauge sentence quality. Based on this, only two optimal conjunctions of the current words are retained in the method to generate… More >

  • Open Access


    SERVQUAL Model Based Evaluation Analysis of Railway Passenger Transport Service Quality in China

    Huiwei Niu1, Jiao Yao1,*, Jing Zhao2, Jin Wang3,4

    Journal on Big Data, Vol.1, No.1, pp. 17-24, 2019, DOI:10.32604/jbd.2019.05799

    Abstract Railway is the backbone of Chinese transportation system, but its poor quality of services for passengers cause complains now and then. This study first analyzed the influencing factors of service quality on railway passenger, and its quality characteristics was also explained, and finally we proposed an evaluation system of service quality on railway passenger transport. Through the statistical analysis and processing of the basic information from survey data from railway station, trains and the official website of the ticket purchase, the evaluation score of question naire was converted into the score in evaluation index system, which was based on SERVQUAL… More >

  • Open Access


    Fuzzy C-Means Algorithm Automatically Determining Optimal Number of Clusters

    Ruikang Xing1,*, Chenghai Li1

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 767-780, 2019, DOI:10.32604/cmc.2019.04500

    Abstract In clustering analysis, the key to deciding clustering quality is to determine the optimal number of clusters. At present, most clustering algorithms need to give the number of clusters in advance for clustering analysis of the samples. How to gain the correct optimal number of clusters has been an important topic of clustering validation study. By studying and analyzing the FCM algorithm in this study, an accurate and efficient algorithm used to confirm the optimal number of clusters is proposed for the defects of traditional FCM algorithm. For time and clustering accuracy problems of FCM algorithm and relevant algorithms automatically… More >

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