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IEEE/ICACT20250013 Slide.12        [Big Slide]	Oral Presentation
	Here we have our proposed ensemble network architecture. Each base model is composed of multiple Conv1D blocks, and time-series data along with metadata are fed into each sub-model. We used three types of pooling layers: average pooling, max pooling, and global average pooling (GAP). Finally, the prediction values from each sub-model are passed to an attention layer that generates the final prediction.

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