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Images counts of garbage classes by split

Images counts of garbage classes by split

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Fig. 1 Example images from Garbage Dataset
Fig. 2 Xception architecture [34]
Fig. 3 Accuracy and F1-score of models Our proposed SE-Xception model...
Fig. 4 Confusion matrix of proposed model The confusion matrix of Fig....
Images counts of garbage classes by split
A Novel SE-Xception Model for Robust Classification of Garbage
Conference Paper
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  • Sep 2024
In this study, we propose a novel deep learning model, SE-Xception, which integrates Squeeze-and-Excitation (SE) blocks into the Xception architecture for solid waste classification. This model is designed to address the growing global challenge of waste accumulation by enhancing the classification accuracy of waste materials. Utilizing a publicly...
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... categories consist of materials such as metal, glass, biological as seen in Fig.1. As presented in Table 1, the categories are divided into train 70%, validation 15% and test 15% to obtain realistic and efficient results. The least data is in the trash category with 834 images, and the most data is in the clothes category with 5325 images. ...