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Xception architecture [34]

Xception architecture [34]

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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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... to process spatial and channel-wise information individually thus resulting in a significant reduction in the model's computational load while still getting the same quality. Its powerful feature in the architecture is that it can describe difficult processes of image classification in a way to explain it by large and varied dataset's ability. Fig. 2 depicts the Xception architecture. Initially, the data passes through the entry flow, followed by the middle flow, which is repeated eight times and concludes with the exit flow. It is important to note that each Convolution and Separable Convolution layer is accompanied by batch ...