apple_2 Computer Vision Project

ack

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Description

Here are a few use cases for this project:

  1. Food Quality Assurance: By using the "apple_2" model in industries related to food production and distribution, food quality can be monitored in an automated manner. For instance, supermarkets or fruit vendors could utilize the model to identify rot in apples before they are sold.

  2. Agricultural Practices: Farmers could use this model to scan their apple orchards, spotting and isolating any rotten apple trees before the rot has a chance to spread to healthy trees.

  3. Waste Management: Garbage sorting facilities could use the "apple_2" model to automatically sort through waste and separate decomposing, organic apple waste from general waste. It can offer a more efficient method in recycling operations or composting initiatives.

  4. Humanitarian Efforts: Non-profit organizations or public services could implement the "apple_2" model in initiatives aimed at redistributing perishable goods to people in need, avoiding waste by identifying rotting apples and creating higher quality control.

  5. Education: The model could be used as part of a teaching tool for botany or horticultural courses, helping students to visually identify signs of rot in apples and understand the underlying causes and management practices.

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{
                            apple_2-ipit3_dataset,
                            title = { apple_2 Dataset },
                            type = { Open Source Dataset },
                            author = { ack },
                            howpublished = { \url{ https://universe.roboflow.com/ack/apple_2-ipit3 } },
                            url = { https://universe.roboflow.com/ack/apple_2-ipit3 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2025-02-26 },
                            }
                        
                    

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