Name: Product recgnition Dataset
License: https://choosealicense.com/licenses/mit/

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Explore Dataset

Here are a few use cases for this project:

Automated Retail Inventory: A "Product Recognition" model can recognize different canned products from images taken in-store and provide precise inventory data. It aids in restocking, keeping track of sales trends, and minimizing human errors in inventory management.
Smart Vending Machines: This model can be implemented into vending machines to automatically identify the type of canned product being dispensed. It would simplify the process of tracking and restocking inventory.
Waste Sorting Applications: The model can help to identify and classify different canned products in waste management centers. This can lead to better recycling strategies, aiding in differentiating recyclable material from each other quickly.
Grocery Shopping Apps: Users can simply take a picture of their empty cans, and the model will identify the product and automatically add it to their shopping list.
Consumer Behavior Analysis: Retailers can use the model in combination with store cameras to gather insights on which products are gaining attention from consumers, by recognizing the product in the customer's hand or shopping cart.

Cite This Project

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

@misc{
                            product-recgnition_dataset,
                            title = { Product recgnition Dataset },
                            type = { Open Source Dataset },
                            author = { kevindroide@gmail.com },
                            howpublished = { \url{ https://universe.roboflow.com/kevindroide-gmail-com/product-recgnition } },
                            url = { https://universe.roboflow.com/kevindroide-gmail-com/product-recgnition },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jun },
                            note = { visited on 2024-05-02 },
                            }