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  • Open Access

    ARTICLE

    A Feature Learning-Based Model for Analyzing Students’ Performance in Supportive Learning

    P. Prabhu1, P. Valarmathie2,*, K. Dinakaran3

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2989-3005, 2023, DOI:10.32604/iasc.2023.028659 - 15 March 2023

    Abstract Supportive learning plays a substantial role in providing a quality education system. The evaluation of students’ performance impacts their deeper insight into the subject knowledge. Specifically, it is essential to maintain the baseline foundation for building a broader understanding of their careers. This research concentrates on establishing the students’ knowledge relationship even in reduced samples. Here, Synthetic Minority Oversampling TEchnique (SMOTE) technique is used for pre-processing the missing value in the provided input dataset to enhance the prediction accuracy. When the initial processing is not done substantially, it leads to misleading prediction accuracy. This research… More >

  • Open Access

    ARTICLE

    Feature Relationships Learning Incorporated Age Estimation Assisted by Cumulative Attribute Encoding

    Qing Tian1,2,3,*, Meng Cao1,2, Tinghuai Ma1,2

    CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 467-482, 2018, DOI:10.3970/cmc.2018.02197

    Abstract The research of human facial age estimation (AE) has attracted increasing attention for its wide applications. Up to date, a number of models have been constructed or employed to perform AE. Although the goal of AE can be achieved by either classification or regression, the latter based methods generally yield more promising results because the continuity and gradualness of human aging can naturally be preserved in age regression. However, the neighbor-similarity and ordinality of age labels are not taken into account yet. To overcome this issue, the cumulative attribute (CA) coding was introduced. Although such More >

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