Name: all_scanned_docs Dataset
License: https://creativecommons.org/publicdomain/zero/1.0/

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Explore Dataset

Here are a few use cases for this project:

"Digital Library Optimization": The "all_scanned_docs" model can be implemented in digital libraries to swiftly categorize and organize the scanned documents based on the metadata, enriching the searching experience for researchers and students.
"Academic Resource Management": Higher education institutions can use the model to automate the sorting and referencing of academic documents like dissertations, theses, project reports, and research papers.
"Legal Document Classification": Government agencies and law firms can implement this model to scan and categorize legal documents quickly, helping to identify and organize specific legal clauses, references, and case numbers.
"Document Verification": HR and recruitment agencies can use this model for filtering through CVs/resumes, certificates, and other professional documents, helping in efficient document verification and applicant screening.
"Automated Publishing House": The model can be incorporated to automate the process in a publishing house, aiding in detailed manuscript analysis, including chapters, figures, tables, references, and more. This could speed up the reviews and proofreading of drafts substantially.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            all_scanned_docs_dataset,
                            title = { all_scanned_docs Dataset },
                            type = { Open Source Dataset },
                            author = { new-workspace-nt9bx },
                            howpublished = { \url{ https://universe.roboflow.com/new-workspace-nt9bx/all_scanned_docs } },
                            url = { https://universe.roboflow.com/new-workspace-nt9bx/all_scanned_docs },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-04-26 },
                            }