دورية أكاديمية

A textual and visual features-jointly driven hybrid intelligent system for digital physical education teaching quality evaluation

التفاصيل البيبلوغرافية
العنوان: A textual and visual features-jointly driven hybrid intelligent system for digital physical education teaching quality evaluation
المؤلفون: Boyi Zeng, Jun Zhao, Shantian Wen
المصدر: Mathematical Biosciences and Engineering, Vol 20, Iss 8, Pp 13591-13601 (2023)
بيانات النشر: AIMS Press, 2023.
سنة النشر: 2023
المجموعة: LCC:Biotechnology
LCC:Mathematics
مصطلحات موضوعية: hybrid intelligent system, textual features, visual features, smart cities, Biotechnology, TP248.13-248.65, Mathematics, QA1-939
الوصف: The utilization of intelligent computing in digital teaching quality evaluation has been a practical demand in smart cities. Currently, related research works can be categorized into two types: textual data-based approaches and visual data-based approaches. Due to the gap between their different formats and modalities, it remains very challenging to integrate them together when conducting digital teaching quality evaluation. In fact, the two types of information can both reflect distinguished knowledge from their own perspectives. To bridge this gap, this paper proposes a textual and visual features-jointly driven hybrid intelligent system for digital teaching quality evaluation. Visual features are extracted with the use of a multiscale convolution neural network by introducing receptive fields with different sizes. Textual features serve as the auxiliary contents for major visual features, and are extracted using a recurrent neural network. At last, we implement the proposed method through some simulation experiments to evaluate its practical running performance, and a real-world dataset collected from teaching activities is employed for this purpose. We obtain some groups of experimental results, which reveal that the hybrid intelligent system developed by this paper can bring more than 10% improvement of efficiency towards digital teaching quality evaluation.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1551-0018
العلاقة: https://doaj.org/toc/1551-0018Test
DOI: 10.3934/mbe.2023606?viewType=HTML
DOI: 10.3934/mbe.2023606
الوصول الحر: https://doaj.org/article/9d4893cf13474c9d919565be3ef2bbdaTest
رقم الانضمام: edsdoj.9d4893cf13474c9d919565be3ef2bbda
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15510018
DOI:10.3934/mbe.2023606?viewType=HTML