Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education
In this paper, we propose an algorithm to identify and solve systems of high-order equations. We rely on traditional solution methods to build algorithms to solve automated equations based on deep learning. The proposal method includes two main steps. In the first step, we use YOLOV4 (Kumar et al. 2...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2021/1682395 |
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| _version_ | 1832552595138281472 |
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| author | Phat Nguyen Huu Khang Doan Xuan |
| author_facet | Phat Nguyen Huu Khang Doan Xuan |
| author_sort | Phat Nguyen Huu |
| collection | DOAJ |
| description | In this paper, we propose an algorithm to identify and solve systems of high-order equations. We rely on traditional solution methods to build algorithms to solve automated equations based on deep learning. The proposal method includes two main steps. In the first step, we use YOLOV4 (Kumar et al. 2020; Canu, 2020) to recognize equations and letters associated with the VGG-16 network (Simonyan and Zisserman, 2015) to classify them. We then used the SymPy model to solve the equations in the second step. Data are images of systems of equations that are typed and designed by ourselves or handwritten from other sources. Besides, we also built a web-based application that helps users select an image from their devices. The results show that the proposed algorithm is set out with 95% accuracy for smart-education applications. |
| format | Article |
| id | doaj-art-cec8bb86e4c14df9ab0f9e24e333822e |
| institution | Kabale University |
| issn | 1687-9732 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Computational Intelligence and Soft Computing |
| spelling | doaj-art-cec8bb86e4c14df9ab0f9e24e333822e2025-02-03T05:58:22ZengWileyApplied Computational Intelligence and Soft Computing1687-97322021-01-01202110.1155/2021/1682395Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-EducationPhat Nguyen Huu0Khang Doan Xuan1School of Electrical and Electronic EngineeringSchool of Electrical and Electronic EngineeringIn this paper, we propose an algorithm to identify and solve systems of high-order equations. We rely on traditional solution methods to build algorithms to solve automated equations based on deep learning. The proposal method includes two main steps. In the first step, we use YOLOV4 (Kumar et al. 2020; Canu, 2020) to recognize equations and letters associated with the VGG-16 network (Simonyan and Zisserman, 2015) to classify them. We then used the SymPy model to solve the equations in the second step. Data are images of systems of equations that are typed and designed by ourselves or handwritten from other sources. Besides, we also built a web-based application that helps users select an image from their devices. The results show that the proposed algorithm is set out with 95% accuracy for smart-education applications.http://dx.doi.org/10.1155/2021/1682395 |
| spellingShingle | Phat Nguyen Huu Khang Doan Xuan Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education Applied Computational Intelligence and Soft Computing |
| title | Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education |
| title_full | Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education |
| title_fullStr | Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education |
| title_full_unstemmed | Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education |
| title_short | Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education |
| title_sort | proposing algorithm using yolov4 and vgg 16 for smart education |
| url | http://dx.doi.org/10.1155/2021/1682395 |
| work_keys_str_mv | AT phatnguyenhuu proposingalgorithmusingyolov4andvgg16forsmarteducation AT khangdoanxuan proposingalgorithmusingyolov4andvgg16forsmarteducation |