test Object Detection Dataset and Pre-Trained Model by utkarsh

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Explore Dataset

Here are a few use cases for this project:

Automatic Invoice Processing: Use the "test" model to extract key information from invoices and receipts for businesses to streamline their accounting procedures. By identifying and capturing the data, the model can automate data entry and reduce manual input errors, saving time and resources.
Expense Management Applications: Integrate the "test" model into expense management apps to help users track their personal or business expenditures. By automatically capturing data from receipts, the apps can create organized reports, categorize expenses, and generate analytics for better financial decision-making.
Tax Preparation and Deduction Tracking: Implement the "test" model in tax preparation software to help users track deductible expenses. By identifying relevant information on receipts, the application can log and categorize deductions, making tax season easier and more efficient for individuals and businesses.
Supply Chain and Inventory Management: Implement the "test" model in supply chain and inventory management systems to track purchases, shipments, and deliveries. The model can identify vendor and shipping information, dates, and item details, ensuring accurate management of goods and smoother operations.
Retail Analytics and Customer Insights: Use the "test" model to analyze purchase patterns and trends within a retail environment. By extracting data from customer receipts, the model can provide insights into popular items, peak purchase times, and customer demographics, assisting retailers with targeted marketing and inventory management.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            test-uib0k_dataset,
                            title = { test Dataset },
                            type = { Open Source Dataset },
                            author = { utkarsh },
                            howpublished = { \url{ https://universe.roboflow.com/utkarsh-cqdp8/test-uib0k } },
                            url = { https://universe.roboflow.com/utkarsh-cqdp8/test-uib0k },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { nov },
                            note = { visited on 2024-04-20 },
                            }