Automatic Asbestos Control Using Deep Learning Based Computer Vision System
The paper discusses the results of the research and development of an innovative deep learning-based computer vision system for the fully automatic asbestos content (productivity) estimation in rock chunk (stone) veins in an open pit and within the time comparable with the work of specialists (about...
Guardado en:
Autores principales: | Vasily Zyuzin, Mikhail Ronkin, Sergey Porshnev, Alexey Kalmykov |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/43a306127d5a434ea9de8243c36fd8d2 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Attention Mask R-CNN for Ship Detection and Segmentation From Remote Sensing Images
por: Xuan Nie, et al.
Publicado: (2020) -
Cascaded Segmented Matting Network for Human Matting
por: Bo Liu, et al.
Publicado: (2021) -
Pixel-Level Analysis for Enhancing Threat Detection in Large-Scale X-ray Security Images
por: Joanna Kazzandra Dumagpi, et al.
Publicado: (2021) -
Developing and Testing a Deep Learning Approach for Mapping Retrogressive Thaw Slumps
por: Ingmar Nitze, et al.
Publicado: (2021) -
The Global Spread of Asbestos
por: Arthur L. Frank, et al.
Publicado: (2014)