Communication Dans Un Congrès Année : 2025

Vision Transformers for X-ray Diffraction Patterns Analysis

Résumé

Understanding materials properties depends largely on the ability to determine its components, and in particular its mineral phases. Powder X-ray diffraction (XRD) is a powerful tool for such purposes. This paper presents a Transformerbased vision model (ViT) for mineral phase identification, and proportion inference to quantify the mineral phases present in a material. Our analysis shows that the tokenization strategy is a critical step for XRD pattern analysis. The results obtained for both tasks are excellent and more robust than those obtained with a CNN. The proposed approach also makes it possible to introduce visualization tools for signal analysis, to better understand how information flows through the model and how data is classified or quantified.

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Dates et versions

hal-05009626 , version 1 (28-03-2025)

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Titouan Simonnet, Mame Diarra Fall, Sylvain Grangeon, Bruno Galerne. Vision Transformers for X-ray Diffraction Patterns Analysis. ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2025, Hyderabad, India. pp.1 - 5, ⟨10.1109/icassp49660.2025.10887635⟩. ⟨hal-05009626⟩
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