@InProceedings{2023_ochoaruiz1171,
	author = "Franscisco Javier Lopez-Tiro and Elias Villalvazo-Avila and Juan Pablo Betancur-Rengifo and Jonathan El-Beze and Jacques Hubert and Gilberto Ochoa-Ruiz and Christian Daul",
	title = "Automated endoscopic stone recognition using a multi-view fusion approach and a two-step transfer learning",
	booktitle = "29° Colloque sur le traitement du signal et des images",
	year = "2023",
	publisher = "GRETSI - Groupe de Recherche en Traitement du Signal et des Images",
	number = "2023-1171",
	pages = "p. 413-416",
	month = "Aout # 6 - Sept # 9",
	address = "Grenoble",
	doi = "",
	pdf = "2023_ochoaruiz1171.pdf",
	abstract = "This contribution presents a deep-learning method for extracting and fusing image information acquired from different viewpoints, with the aim to produce more discriminant object features for the identification of the type of kidney stones seen in endoscopic images. The model was further improved with a two-step transfer learning approach and by attention blocks to refine the learned feature maps. These deep feature fusion strategies improved the results of single view extraction backbone models by more than 6% in terms of accuracy of the kidney stones classification..pdf",
}