annotations_factures Computer Vision Project

genuine

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Classes (30)
ICE
account_number
additional_info
customer_address
customer_billing_address
customer_email
customer_id
customer_name
customer_phone_number
customer_service
customer_shipping_address
customer_website
delivery_fee
discount
invoice_date_issue
invoice_due_date
invoice_id
price products
subtotal
supplier_address
supplier_date_issue
supplier_email
supplier_email_address
supplier_name
supplier_phone_number
supplier_website
tax
tax_rate
total
Description

Here are a few use cases for this project:

  1. Financial Auditing: This model could be used by both internal and external auditors to simplify the auditing process. By analyzing massive amounts of invoices, it can reduce time and increase accuracy by automatically classifying the required information.

  2. Expense Management: Companies can use this model to manage expense accounts. They could easily extract and classify the information of any incoming invoice, which can be used to monitor operational costs, track expenses, and ensure accurate record keeping.

  3. Supplier Management: This model can be used to manage and analyze supplier information for procurement and supply chain departments. It can extract and classify data related to suppliers such as their addresses, phone numbers, or emails, which could be useful for vendor management.

  4. Customer Relationship Management (CRM): The ability to extract customer information from invoices could be leveraged for customer relationship management. This data could enhance understanding of customer buying behaviors and aid in improving customer service.

  5. E-commerce Platforms: Online selling platforms can use this model to manage transactions and understand purchasing behaviors by extracting key information from customer invoices. The data obtained could be used for business analytics, customer segmentation, and targeted marketing strategies.

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{
                            annotations_factures_dataset,
                            title = { annotations_factures Dataset },
                            type = { Open Source Dataset },
                            author = { genuine },
                            howpublished = { \url{ https://universe.roboflow.com/genuine/annotations_factures } },
                            url = { https://universe.roboflow.com/genuine/annotations_factures },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-11-24 },
                            }
                        
                    

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