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DC Field | Value | Language |
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dc.contributor.advisor | Sasidhar, P S Kalyan | |
dc.contributor.author | Mehta, Kavisha | |
dc.date.accessioned | 2020-09-22T17:10:37Z | |
dc.date.available | 2023-02-17T17:10:37Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Mehta, Kavisha (2020). Recognic console. Dhirubhai Ambani Institute of Information and Communication Technology. vii, 34 p. (Acc.No: T00900) | |
dc.identifier.uri | http://drsr.daiict.ac.in//handle/123456789/985 | |
dc.description.abstract | Users 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.subject | Vision OCR | |
dc.subject | Analytics | |
dc.subject | Data Pipeline | |
dc.subject | API | |
dc.subject | Database Connectors | |
dc.classification.ddc | 005.7585 MEH | |
dc.title | Recognic console | |
dc.type | Dissertation | |
dc.degree | M. Tech | |
dc.student.id | 201811080 | |
dc.accession.number | T00900 | |
Appears in Collections: | M Tech Dissertations |
Files in This Item:
File | Description | Size | Format | |
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201811080.pdf Restricted Access | 464.49 kB | Adobe PDF | View/Open Request a copy |
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