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<resource xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns='http://datacite.org/schema/kernel-3' xsi:schemaLocation='http://datacite.org/schema/kernel-3 http://schema.datacite.org/meta/kernel-3/metadata.xsd'>
<creators>
<creator>
<creatorName>Hristea, I.</creatorName>
<affiliation>Universitatea "Alexandru Ioan Cuza", Iaşi, România</affiliation>
</creator>
<creator>
<creatorName>Iftene, A.</creatorName>
<affiliation>Universitatea "Alexandru Ioan Cuza", Iaşi, România</affiliation>
</creator>
</creators>
<titles>
<title xml:lang='en'>OCR: Handwrite Recognition</title>
</titles>
<publisher>Instrumentul Bibliometric National</publisher>
<publicationYear>2022</publicationYear>
<relatedIdentifier relatedIdentifierType='ISBN' relationType='IsPartOf'>978-9975-68-461-3</relatedIdentifier>
<subjects>
<subject>computer vision</subject>
<subject>OCR</subject>
<subject>Convolutional Network.</subject>
</subjects>
<dates>
<date dateType='Issued'>2022</date>
</dates>
<resourceType resourceTypeGeneral='Text'>Conference Paper</resourceType>
<descriptions>
<description xml:lang='en' descriptionType='Abstract'><p>Computer Vision aids the computer in comprehending what occurs in a visual representation of the real world, such as videos or photographs. A subfield of Computer Vision is Optical Character Recognition, which works with handwritten or printed material that is converted into machine-readable language. All of the world&rsquo;s paper-based documents could be translated into a more convenient format for storage without having to rewrite them. The purpose of this paper is to develop an algorithm that can convert a picture of handwritten text on paper into a machinereadable format, making it easier for individuals to keep papers.</p></description>
</descriptions>
<formats>
<format>application/pdf</format>
</formats>
</resource>