Deep Learning for Automatic Vision-based Recognition of Industrial Surface Defects: a Survey

Deep Learning for Automatic Vision-based Recognition of Industrial Surface Defects: a Survey

Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted feature extraction, selection, and validation, counted on a...

Full description

Bibliographic Details
Main Authors: Bevilacqua, V. (Author), Brunetti, A. (Author), Buongiorno, D. (Author), Carli, R. (Author), Dotoli, M. (Author), Longo, N. (Author), Prunella, M. (Author), Scardigno, R.M (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Subjects:
Artificial intelligence
Artificial Vision
Auto-Encoder
Automatic Recognition
Autonomous systems
Computer vision
Convolutional Neural Network
Deep learning
Deep Learning
Explainable Artificial Intelligence
Feature Attention Mechanism
Feature extraction
Generative adversarial networks
Generative-Adversarial Network
Image recognition
Industrial Surface Defects
Inspection
Manuals
Transfer learning
Transfer Learning
Online Access:View Fulltext in Publisher
View in Scopus

Internet

View Fulltext in Publisher
View in Scopus

Similar Items