Waste-Classification and CNN-Plastic-Waste-Classification

These two tools are competitors, as both are deep learning-based CNN models designed for classifying waste into recyclable and non-recyclable categories, with the former having a broader scope (organic or recyclable) and higher community engagement.

Maintenance 0/25
Adoption 5/25
Maturity 16/25
Community 14/25
Maintenance 0/25
Adoption 3/25
Maturity 16/25
Community 14/25
Stars: 9
Forks: 3
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 3
Forks: 3
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About Waste-Classification

aniass/Waste-Classification

Waste image classification into organic or recyclable ones with CNN algorithm.

This tool helps individuals or organizations sort waste more effectively by classifying images of trash as either organic or recyclable. You provide an image of a waste item, and the tool tells you its category, assisting with proper disposal. This is ideal for anyone managing waste, from homeowners to facility managers, who wants to improve recycling accuracy.

waste-management recycling sustainability waste-sorting environmental-stewardship

About CNN-Plastic-Waste-Classification

Hardik-Sankhla/CNN-Plastic-Waste-Classification

A deep learning-based Plastic Waste Classification system using Convolutional Neural Networks (CNNs) to categorize waste into recyclable and non-recyclable materials. This project aims to support sustainable waste management by leveraging AI-powered image classification.

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