Recognition and Solution of Handwritten Partial Differential Equation Using Deep Learning | ||||
| The International Undergraduate Research Conference | ||||
| Volume 6, Issue 6, September 2022, Page 1-5 PDF (543.91 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/iugrc.2022.302479 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Ahmed Yehia; Mohamed Magdy; Amr Ashraf; Mahmoud Gamal; Mohanad Walid | ||||
| Military Technical College, Cairo, Egypt. | ||||
| Abstract | ||||
| Water pollution is one of the leading environmental issues faced especially at developing countries all over the World. However, the study of pollution movement is a necessary basis for solving water quality problems. As there is a great development in the technologies of Artificial Intelligence So it can be used for solving handwritten partial differential equation of water quality problems. The problem of handwritten mathematical expression recognition is one of the complicated issue in the area of computer vision research. Segmentation and classification of specific character makes the task more difficult. In this paper, groups of handwritten Advection Partial differential equations are considered to recognize and make a solution for those equations. Horizontal compact projection analysis and combined connected component analysis methods are used for segmentation. For classification of specific character, we apply Convolutional Neural Network. Each of the correct detection, Nangs algorithm is used for the solution of the equation. Finally, the experimental results show the great effectiveness of our proposed system. | ||||
| Keywords | ||||
| Character segmentation; Convolutional neural Network; Projection analysis; Advection equation; Connected component; Partial differential equation; Nangs | ||||
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