Finding defects during production is crucial in industrial manufacturing. While various detection methods exist, this paper proposes a short review on techniques based on visual saliency. Saliency approaches try to mimic how humans see and are characterized by advantages such as accuracy, speed, and ability to handle complex situations. With solutions based on deep learning becoming increasingly dominant, this review aims to provide a brief analysis of the current state of research in this field, possibly stimulating continued exploration and development of new techniques.
Visual Saliency Approaches for Defect Detection in Industrial Processes: A Short Review
Marco Porta
2024-01-01
Abstract
Finding defects during production is crucial in industrial manufacturing. While various detection methods exist, this paper proposes a short review on techniques based on visual saliency. Saliency approaches try to mimic how humans see and are characterized by advantages such as accuracy, speed, and ability to handle complex situations. With solutions based on deep learning becoming increasingly dominant, this review aims to provide a brief analysis of the current state of research in this field, possibly stimulating continued exploration and development of new techniques.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
