Conditional image-to-image translation generative adversarial network (cGAN) for fabric defect data augmentation
Swash Sami Mohammed,
Hülya Gökalp Clarke
Abstract:The availability of comprehensive datasets is a crucial challenge for developing artificial intelligence (AI) models in various applications and fields. The lack of large and diverse public fabric defect datasets forms a major obstacle to properly and accurately developing and training AI models for detecting and classifying fabric defects in real-life applications. Models trained on limited datasets struggle to identify underrepresented defects, reducing their practicality. To address these issues, this study… Show more
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