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dc.contributor.advisorSasidhar, P S Kalyan
dc.contributor.authorMehta, Kavisha
dc.date.accessioned2020-09-22T17:10:37Z
dc.date.available2023-02-17T17:10:37Z
dc.date.issued2020
dc.identifier.citationMehta, Kavisha (2020). Recognic console. Dhirubhai Ambani Institute of Information and Communication Technology. vii, 34 p. (Acc.No: T00900)
dc.identifier.urihttp://drsr.daiict.ac.in//handle/123456789/985
dc.description.abstractUsers leave behind a large amount of data in digital footprints across different channels of engagement & consumption of products & services. Enterprises & governments are investing to adopt technology for efficiently extracting meaningful information from documents that are collected at the source. Traditionally this has been back-office operations & the turnaround time has been spread from a few days to several weeks for absorbing this information & performing certain logical analysis. Recognic identifies, understands & validates the information in various formats from complex document structures&simplifies digital document processing. Recognic is the future of indexing, organizing, storing & extracting intelligence from the documents. The product is designed to understand and extract useful information from complex document structures & parse the information in an easy to ingest JSON, XML, CSV format, or any other legacy databases. It also comes bundled with a smart analytics component to give extraction confidence insights on the documents parsed through it. Hence this M-Tech Project is focused to build a smart analytics dashboard that helps in providing a connected user-experience on top of the core API Product.
dc.subjectVision OCR
dc.subjectAnalytics
dc.subjectData Pipeline
dc.subjectAPI
dc.subjectDatabase Connectors
dc.classification.ddc005.7585 MEH
dc.titleRecognic console
dc.typeDissertation
dc.degreeM. Tech
dc.student.id201811080
dc.accession.numberT00900


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