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Recognition of handwritten characters in digital images using context-based machine learning
Recognition of handwritten characters in digital images using context-based machine learning
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机译:使用基于上下文的机器学习识别数字图像中的手写字符
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摘要
Methods and apparatuses are described for of recognizing handwritten characters in digital images using context-based machine learning. A server captures an image of a document that comprises one or more handwritten data fields, the document associated with a user identifier. The server identifies a field type for each handwritten data field in the image. The server creates a pixel intensity array for each character in each handwritten data field and determines whether a user-specific character map exists for the user identifier. If a map exists, the server retrieves the map and generates digital form data by executing a user-specific handwriting classifier using the map, the pixel intensity arrays, and the field types. If a map does not exist, the server builds a map based upon the pixel intensity arrays and generates digital form data by executing a baseline handwriting classifier using the map, the pixel intensity arrays, and the field types.
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