Smart Defect Detection in Aero-Engines: Evaluating Transfer Learning with VGG19 and Data-Efficient Image Transformer Models

Smart Defect Detection in Aero-Engines: Evaluating Transfer Learning with VGG19 and Data-Efficient Image Transformer Models

This study explores the impact of transfer learning on enhancing deep learning models for detecting defects in aero-engine components. We focused on metrics such as accuracy, precision, recall, and loss to compare the performance of models VGG19 and DeiT (data-efficient image transformer). RandomSea...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Samira Mohammadi, Vahid Rahmanian, Sasan Sattarpanah Karganroudi, Mehdi Adda
Format: Artykuł
Język:English
Wydane: MDPI AG 2025-01-01
Seria:Machines
Hasła przedmiotowe:
transfer learning
defect detection
aero-engine components
transformer models
deep learning
Dostęp online:https://www.mdpi.com/2075-1702/13/1/49

Internet

https://www.mdpi.com/2075-1702/13/1/49

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