Abstract
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.
Highlights
Artificial intelligence (AI) has created a revolution in society with the remarkable development of science and technology, especially since their explosion. e applications of artificial intelligence (AI) are applied to many aspects of life that make human life more and more comfortable. ere are many applications of AI and deep learning, for example, Google translate tool, facial recognition system, cancer detection through X-ray pictures, self-driving cars of Tesla, and smart-education applications. ese are very practical applications for life
Testing of values is difficult to perform by hand. erefore, we completely solve this difficult problem by computer vision with the current development of deep learning (DL)
Identifying and solving problems about equations and systems of high-order equations is one of many practical applications of DL [6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]. e solutions are deployed on many applications such as Quanda, Photomath, and Mathway with millions of users on iOS and Android
Summary
Artificial intelligence (AI) has created a revolution in society with the remarkable development of science and technology, especially since their explosion. e applications of AI are applied to many aspects of life that make human life more and more comfortable. ere are many applications of AI and deep learning, for example, Google translate tool, facial recognition system, cancer detection through X-ray pictures, self-driving cars of Tesla, and smart-education applications. ese are very practical applications for life. Solving equations is a fundamental problem involving many different applications for learning and researching process. Erefore, we completely solve this difficult problem by computer vision with the current development of deep learning (DL). The authors [1] use the YOLOv4 model to optimize the speed and accuracy of objects while detecting them. E results show that the model is suitable for detecting objects at a real-time speed of 65 frames per second (FPS) on the Tesla V100, accuracy is not good with 43.5% AP and 65.7% AP50 for the MS COCO dataset. Erefore, we use YOLOv4, an algorithm that has been evaluated to be highly feasible [3, 4], to identify equations in the identification block.
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