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Communication Dans Un Congrès Année : 2022

An hybrid cnn-transformer model based on multi-feature extraction and attention fusion mechanism for cerebral emboli classification

Résumé

When dealing with signal processing and deep learning for classification, the choice of inputting whether the raw signal or transforming it into a time-frequency representation (TFR) remains an open question. In this work, we propose a novel CNN-Transformer
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Dates et versions

hal-04429525 , version 1 (31-01-2024)

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  • HAL Id : hal-04429525 , version 1

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Philippe Delachartre, Yamil Vindas, Emmanuel Roux, Blaise Kévin Guépié, Marilys Almar. An hybrid cnn-transformer model based on multi-feature extraction and attention fusion mechanism for cerebral emboli classification. Machine Learning for Healthcare, Aug 2022, Durham, United States. ⟨hal-04429525⟩
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