Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
37th (2023)
Session ID : 1O3-GS-7-02
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Recycle Resources Classification using Image Recognition for Recycling Education Support System
*Siyun HUANGKen TSUTSUGUCHI
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

The purpose of this study is to develop an educational application for children to identify recyclable resources from waste images taken by mobile terminals. CNN-based transfer learning was used in the classification of images taken from actual household waste. We developed the original dataset ``STE'' and compared to TrashNet dataset. The classification accuracy varied depending on the types of waste, where ``paper'' or ``plastic'' waste was found to have relatively high accuracy in our STE dataset, particularly after background removal.

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© 2023 The Japanese Society for Artificial Intelligence
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