A Data-Centric Approach to Design and Analysis of a Surface-Inspection System Based on Deep Learning in the Plastic Injection Molding Industry
Manufacturers are eager to replace the human inspector with automatic inspection systems to improve the competitive advantage by means of quality. However, some manufacturers have failed to apply the traditional vision system because of constraints in data acquisition and feature extraction. In this...
Guardado en:
Autores principales: | Donggyun Im, Sangkyu Lee, Homin Lee, Byungguan Yoon, Fayoung So, Jongpil Jeong |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/9cf7e32a84c64e71944e3f7211716fb1 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
R-CNN-Based Large-Scale Object-Defect Inspection System for Laser Cutting in the Automotive Industry
por: Donggyun Im, et al.
Publicado: (2021) -
Cysticercosis occurrence and sanitary risks in groups of inspected and non-inspected swine in Brazil
por: DE ARRUDA PINTO,PAULO SÉRGIO, et al.
Publicado: (2002) -
Deep Convolutional Neural Network Optimization for Defect Detection in Fabric Inspection
por: Chao-Ching Ho, et al.
Publicado: (2021) -
Ginger Seeding Detection and Shoot Orientation Discrimination Using an Improved YOLOv4-LITE Network
por: Lifa Fang, et al.
Publicado: (2021) -
Analysis of the Possibilities of Tire-Defect Inspection Based on Unsupervised Learning and Deep Learning
por: Ivan Kuric, et al.
Publicado: (2021)