Multi-Stream Deep Convolutional Neural Network for PET Preform Surface Defects Detection and Classification
Due to the influence of technology factors, various defects will appear in the production process of PET (Polyethylene Terephthalate) preform, and affect the PET preform quality. In order to meet the requirements of the quality inspection efficiency and accuracy for PET preform, a novel multi-stream...
Guardado en:
Autores principales: | Taochuan Zhang, Chunmei Duan |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/a812badf342d42c1a5d6dacfc27338b7 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Fabrication and Mechanical Performance of Non-Crimp Unidirectional Jute-Yarn Preform-Based Composites
por: Yeasin Ali, et al.
Publicado: (2021) -
Mesiodistal Width in Temporary Molars of Chilean Children of Concepción and his Correlation with Standard Preformed Steel Crowns
por: Torres Chianale,María Francisa, et al.
Publicado: (2010) -
FPGA Realization of Two-DimensionalWavelet and Wavelet Packet Transform
por: Mohammed N. Al-Turfi, et al.
Publicado: (2005) -
A New Convolutional Kernel Classifier for Hyperspectral Image Classification
por: Mohsen Ansari, et al.
Publicado: (2021) -
Intrusion Detection System Based on Fast Hierarchical Deep Convolutional Neural Network
por: Robson V. Mendonca, et al.
Publicado: (2021)