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Eternal-MAML: Cross-Domain Defect Recognition by geodezister is a document available to read on EtoBox.

What is Eternal-MAML: Cross-Domain Defect Recognition about?

The document presents Eternal-MAML, a novel meta-learning framework designed to enhance cross-domain defect recognition in industrial products, addressing challenges such as data scarcity and overfitting. By improving the Model-Agnostic Meta-Learning (MAML) approach, Eternal-MAML incorporates a meta-vector for classifier updates and integrates advanced feature extraction techniques to boost generalization accuracy. Experimental results demonstrate that Eternal-MAML outperforms existing methods in defect rec

Author

geodezister

Language

EN