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Proposer
Cristina Turcanu
Title
Classification of Recyclable Waste Using Machine Learning
Goal
The goal of this project is to develop an intelligent, real-time waste classification system using Machine Learning (such as Convolutional Neural Networks) to accurately detect and sort recyclable materials such as paper, plastic, etc using a dataset.
Description
The system aims to improve the efficiency of waste management and support sustainable recycling practices.
Resources
Potential datsaset: www.kaggle.com/datasets/raijincheng/rethink-recycle-dataset?resource=download
Background
Url
Difficulty Level
Challenging
Ethical Approval
None
Number Of Students
2
Supervisor
Cristina Turcanu
Keywords
convolutional neural network (cnn) image recognitioreal-time detection, smart waste sorting, sustainable recycling, computer vision, intelligent system, deep learning
Degrees
Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Science in Artificial Intelligence
Master of Science in Computer Science for Cyber Security
Master of Science in Data Science
Master of Science in Information Technology (Business)
Master of Science in Information Technology (Software Systems)
Master of Science in Network Security
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Bachelor of Science in Computer Science (Cyber Security)
BSc Data Sciences
MSc Applied Cyber Security
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