A way of embedded learning convolution neural network(ELCNN) based on the image content is proposed to evaluate the image aesthetic quality in this paper. Our approach can not only solve the problem of small-scale dat...A way of embedded learning convolution neural network(ELCNN) based on the image content is proposed to evaluate the image aesthetic quality in this paper. Our approach can not only solve the problem of small-scale data but also score the image aesthetic quality. First, we chose Alexnet and VGG_S to compare for confirming which is more suitable for this image aesthetic quality evaluation task. Second, to further boost the image aesthetic quality classification performance, we employ the image content to train aesthetic quality classification models. But the training samples become smaller and only using once fine-tuning cannot make full use of the small-scale data set. Third, to solve the problem in second step, a way of using twice fine-tuning continually based on the aesthetic quality label and content label respective is proposed, the classification probability of the trained CNN models is used to evaluate the image aesthetic quality. The experiments are carried on the small-scale data set of Photo Quality. The experiment results show that the classification accuracy rates of our approach are higher than the existing image aesthetic quality evaluation approaches.展开更多
Based on the related theories and research results of learning behavioral engagement,this study constructed an evaluation framework of learning behavioral engagement in live teaching,which included 24 indicators in th...Based on the related theories and research results of learning behavioral engagement,this study constructed an evaluation framework of learning behavioral engagement in live teaching,which included 24 indicators in three dimensions:compliance with norms,learning participation and social participation.A small-class live English learning for younger students on the ClassIn was taken as a case study program.Five younger students attended this English learning course of 16 lessons totaling 950 minutes.The preset indicators were preliminarily examined based on the teaching records and the recorded course data.Then,experts in the field of educational technology were invited to develop the learning behavioral engagement dimensions and indicator weightings by using the Analytic Hierarchy Process,and to determine the evaluation indicator system for the evaluation of learning behavioral engagement.Finally,based on this framework,the characteristics of learning behavioral engagement of the case course were analyzed,and the influences of students’individual factors,teaching and environmental factors on learning behavioral engagement in live teaching were investigated.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61271361,61163019,61462093 and 61761046)the Research Foundation of Yunnan Province(Nos.2014FA021 and 2014FB113)the Digital Media Technology Key Laboratory of Universities in Yunnan Province
文摘A way of embedded learning convolution neural network(ELCNN) based on the image content is proposed to evaluate the image aesthetic quality in this paper. Our approach can not only solve the problem of small-scale data but also score the image aesthetic quality. First, we chose Alexnet and VGG_S to compare for confirming which is more suitable for this image aesthetic quality evaluation task. Second, to further boost the image aesthetic quality classification performance, we employ the image content to train aesthetic quality classification models. But the training samples become smaller and only using once fine-tuning cannot make full use of the small-scale data set. Third, to solve the problem in second step, a way of using twice fine-tuning continually based on the aesthetic quality label and content label respective is proposed, the classification probability of the trained CNN models is used to evaluate the image aesthetic quality. The experiments are carried on the small-scale data set of Photo Quality. The experiment results show that the classification accuracy rates of our approach are higher than the existing image aesthetic quality evaluation approaches.
基金This article results from Year 2019 project“Online Learning Engagement Analysis Technology and Evaluation Model Based on Three-Layer Space Multidimensional Time Features”(Project No.:61977011)sponsored by National Natural Science Foundation of China(NSFC)+1 种基金from Year 2019 standard pre-research project“Online Course Elements and Evaluation Indicators Based on National Distance Education Public Service System”(Project No.:CELTS-201902)funded by China e-Learning Technology Standardization Committee(CELTSC).
文摘Based on the related theories and research results of learning behavioral engagement,this study constructed an evaluation framework of learning behavioral engagement in live teaching,which included 24 indicators in three dimensions:compliance with norms,learning participation and social participation.A small-class live English learning for younger students on the ClassIn was taken as a case study program.Five younger students attended this English learning course of 16 lessons totaling 950 minutes.The preset indicators were preliminarily examined based on the teaching records and the recorded course data.Then,experts in the field of educational technology were invited to develop the learning behavioral engagement dimensions and indicator weightings by using the Analytic Hierarchy Process,and to determine the evaluation indicator system for the evaluation of learning behavioral engagement.Finally,based on this framework,the characteristics of learning behavioral engagement of the case course were analyzed,and the influences of students’individual factors,teaching and environmental factors on learning behavioral engagement in live teaching were investigated.
