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Text Recognition (OCR) for Patient Records Digitization using CNN BY ONG ZI LEONGA REPORT SUBMITTED TO Universiti Tunku Abdul Rahman in partial fulfillment of the requirements For the degree of BACHELOR
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Individuals seeking to convert old documents into editable text.
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Organizations with large volumes of paperwork that need archiving.
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Text recognition OCR (Optical Character Recognition) is used to convert different types of documents, such as scanned paper documents, PDF files, or images captured by a digital camera, into editable and searchable data.
Individuals and businesses that need to digitize documents for easier storage, editing, and retrieval may require text recognition OCR. This can include administrative professionals, archivists, and businesses needing to process large volumes of documents.
To use text recognition OCR, you first need to upload or scan the document you wish to convert. Then, use OCR software to process the document, allowing it to recognize and extract text. Review and edit the output for accuracy, and finally, save or export the data in your desired format.
The purpose of text recognition OCR is to automate the extraction of printed or handwritten text from physical documents into a digital format, facilitating better data management, accessibility, and organization.
When using text recognition OCR, it is essential to report the original text accurately, any formatting, and any data correction made during the recognition process. Additionally, metadata such as the date of processing and any relevant document identifiers may also be reported.
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