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- W4385730401 abstract "The authors believe that for society to continue improving, it needs to have a better waste classification system. This paper presents a computer vision model trained with a novel dataset comprising images of waste collected from Thailand, aimed at improving computer vision-based waste classification. We compare several CNN models, including VGG16, DenseNet169, ResNet-101, MobileNetV2, and InceptionV3 by using the Trashnet dataset developed by Gary Thung and our novel dataset. Our findings demonstrate that our model trained with both the Trashnet dataset and our new dataset outperforms the model trained by either dataset alone. The authors also discuss how this novel dataset can be improved to provide better results." @default.
- W4385730401 created "2023-08-11" @default.
- W4385730401 creator A5011883315 @default.
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- W4385730401 date "2023-06-28" @default.
- W4385730401 modified "2023-10-17" @default.
- W4385730401 title "Comparison of CNN Models for Urban Garbage Image Classification in Thailand" @default.
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- W4385730401 doi "https://doi.org/10.1109/jcsse58229.2023.10202123" @default.
- W4385730401 hasPublicationYear "2023" @default.
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