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- W4281397017 abstract "Handwritten recognition has achieved tremendous success in the real world. It has various applications such as equation solver, automation, etc. Researchers have proven how recognition of handwritten language characters is done by using a three-step procedure using machine learning algorithms. Moreover, the OCR method allows converting data from physical to digital. Machine learning algorithms like SVM, K-means, Naive Bayes, Decision Trees are used for text recognition. Recognizing handwritten text is a big challenge as the handwriting style of the person can vary from time to time. Poor resolution of the image will lead to inaccurate text recognition. With the increase in advancements, researchers found deep learning models are providing better efficiency than machine learning models. Deep Learning is providing better accuracy for image segmentation, object detection, speech recognition, and image classification as well. Handwritten mathematical equation solving has been implemented using the CNN model. This system is solving offline handwritten polynomial equations using Deep Learning CNN model." @default.
- W4281397017 created "2022-05-25" @default.
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- W4281397017 date "2022-04-28" @default.
- W4281397017 modified "2023-09-30" @default.
- W4281397017 title "SnapSolve — A Novel Mathematics Equation Solver using Deep Learning" @default.
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- W4281397017 doi "https://doi.org/10.1109/icoei53556.2022.9776654" @default.
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