Base detection Object Detection Dataset and Pre-Trained Model by Tiago Henrique Rodrigues Pedrosa Goncalves

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Explore Dataset

Here are a few use cases for this project:

Warehouse Inventory Management: The "Base detection" solution can be deployed in warehouse management systems to identify and categorize inventory using barcodes, qr codes, or numbers. It could be used to rapidly sort through items, verify inventory, or streamline the order fulfillment process.
Manufacturing Quality Control: In manufacturing industries, the model can be used for detecting different base classes on manufactured items. For instance, detecting and categorizing pipe types, identifying product series using barcodes, or detecting any flaws or issues in the small/large bases.
Retail Store Operations: Retail stores can apply this model for instant product identification, price checking, or stock updates. The model can identify products by their barcodes, qr codes, or numbers, thereby automating various retail operations.
Advertising Analytics: The "Base detection" model can be used in ad monitoring systems to identify and categorize banner ads. It can extract key information such as qr codes, numbers, or other special images or texts from the banners, providing valuable data for advertising analytics.
Document Management Systems: The model can be used to organize and classify documents or archival material using qr codes, numbers, or barcodes. It could significantly improve search, retrieval, and classification processes in large document databases.

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{
                            base-detection_dataset,
                            title = { Base detection Dataset },
                            type = { Open Source Dataset },
                            author = { Tiago Henrique Rodrigues Pedrosa Goncalves },
                            howpublished = { \url{ https://universe.roboflow.com/tiago-henrique-rodrigues-pedrosa-goncalves-aznuf/base-detection } },
                            url = { https://universe.roboflow.com/tiago-henrique-rodrigues-pedrosa-goncalves-aznuf/base-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { feb },
                            note = { visited on 2024-04-28 },
                            }