Name: Food Waste Detection V2 Dataset
License: https://creativecommons.org/licenses/by/4.0/

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Explore Dataset

Here are a few use cases for this project:

Restaurant Inventory Management: The model can be used to track and monitor the consumption of food in restaurants. By identifying what food is leftover on customers' plates, restaurants can better understand what items are commonly wasted and optimize their menu accordingly to reduce food waste.
Waste Reduction in Cafeterias: School or corporate cafeterias could utilize this model to measure food waste and modify their food offerings. By identifying and quantifying wasted food, they can adjust portion sizes or take other measures to minimize food waste.
Foster Sustainable Behavior: An app could be developed for individuals to track their food waste at home with the help of this model. This could foster more sustainable behavior by making individuals aware of the amount and types of food they commonly waste.
Food Waste in Events: Event organizers can use this model to detect and quantify food waste during large-scale events. The insights gained can be used to adjust food ordering and portion sizes in future events.
Food Production: Food producers or suppliers can use this model to understand which food products are frequently wasted. This valuable information could be used to adjust their production and supply chain to minimize waste.

Cite This Project

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

@misc{
                            food-waste-detection-v2-fevnw_dataset,
                            title = { Food Waste Detection V2 Dataset },
                            type = { Open Source Dataset },
                            author = { jshort@college.harvard.edu },
                            howpublished = { \url{ https://universe.roboflow.com/jshort-college-harvard-edu/food-waste-detection-v2-fevnw } },
                            url = { https://universe.roboflow.com/jshort-college-harvard-edu/food-waste-detection-v2-fevnw },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2021 },
                            month = { dec },
                            note = { visited on 2024-05-01 },
                            }