IA-SeReOs, an interdisciplinary project towards the automatic segmentation of CT-scanned ancient bone remains
CLÉMENT, Michaël
Institut Polytechnique de Bordeaux [Bordeaux INP]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
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Institut Polytechnique de Bordeaux [Bordeaux INP]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Langue
en
Communication dans un congrès
Ce document a été publié dans
1st international conference on artificIAl Intelligence and applied MAthematics for History and Archaeology, 1st international conference on artificIAl Intelligence and applied MAthematics for History and Archaeology, IAMAHA : 1st international conference on artificIAl Intelligence and applied MAthematics for History and Archaeology, 2023-11-27, Nice.
Résumé en anglais
We present a project shared by biological anthropologists and computer scientists aimed at developing a deep learning method for the analysis of ancient bones scanned by X-ray microtomography. The IA-SeReOs project builds ...Lire la suite >
We present a project shared by biological anthropologists and computer scientists aimed at developing a deep learning method for the analysis of ancient bones scanned by X-ray microtomography. The IA-SeReOs project builds upon previous work by two of the co-authors that proposed a segmentation convolutional neural network, presenting the particularity to enforce the preliminary recognition of bone regions vs sediment rich regions.< Réduire
Mots clés en anglais
Osteology
Deep learning
Computer 3D vision
Origine
Importé de halUnités de recherche