OCR-trained Computer Vision Project

Xerosum

Updated 2 years ago

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Classes (11)
OMRON_address
OMRON_name
bill_to
company_chop
currency
date
invoice_no
ship_to
table
total_amount
vendor_name
Description

Here are a few use cases for this project:

  1. Automating Accounting Processes: The OCR-trained model can be utilized in automating the input of invoice details into accounting software. This allows for quicker, more accurate data entry, reducing human error.

  2. Invoice Management Systems: OCR-trained can serve as a part of an advanced invoice management system that manages and organizes invoices from multiple vendors. This can simplify invoice tracking and payment processes.

  3. Compliance and Audit: This model can be used to verify the accuracy of invoice information for compliance and audit purposes. It can identify key details like date, total amount, vendor name, etc., which can then be compared against recorded transactions.

  4. Paperless Office Transition: Businesses seeking to transition to a paperless environment can utilize this model to digitize their existing paper invoices. This helps in efficient document management and promotes environmental sustainability.

  5. Data Extraction for Analytics: The model can also be employed to extract data from invoices for data analysis. This could help in building predictive models, analyzing spending patterns, and optimizing vendor selection.

Supervision

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Cite This Project

LICENSE
CC BY 4.0

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

                        @misc{
                            ocr-trained_dataset,
                            title = { OCR-trained Dataset },
                            type = { Open Source Dataset },
                            author = { Xerosum },
                            howpublished = { \url{ https://universe.roboflow.com/xerosum/ocr-trained } },
                            url = { https://universe.roboflow.com/xerosum/ocr-trained },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-12-24 },
                            }
                        
                    

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