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Regular version of the site

Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Anton Poluianov
Recyclable Waste Classification Based on Machine Learning
System and Software Engineering
(Master’s programme)
2019
The research concerns waste classification problem using CNNs and smartphone camera for on-device classification. The waste is classified into 6 categories: cardboard, glass, metal, paper, plastic, trash. The dataset chosen is formed from TrashNet and openrecycle datasets. The neural network model selection is based model’s inference time and accuracy. As a result of the experiments MobileNet model was chosen, it achieved 91% accuracy on the dataset. The model was then converted to CoreML model and was implemented on iOS mobile device for real time classification.

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