A new classification algorithm for low concentration slurry based on machine vision
Abstract Machine vision was utilized in this study to accurately classify the low concentration slurry. Orthogonal experiment L9(34) indicated that the optimal coal slurry collection images were achieved with exposure value of 10, slurry layer thickness of 7 cm, and light intensity of 5 × 104 lux. S...
Saved in:
Main Authors: | Chuanzhen Wang, Xinyi Wang, Andile Khumalo, Fengcheng Jiang, Jintao Lv |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2024-12-01
|
Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-024-83765-x |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
ViT-DualAtt: An efficient pornographic image classification method based on Vision Transformer with dual attention
by: Zengyu Cai, et al.
Published: (2024-12-01) -
Impacts of different pig slurry application methods on soil quality indicators in a maize-soybean cropping sequence in the Sub-humid Pampas of Argentina
by: Vanesa Pegoraro, et al.
Published: (2020-09-01) -
Influence of coal gangue-aeolian sand aggregate gradation on rheological properties and pipeline transportation characteristics of filling slurry
by: Bo Liu, et al.
Published: (2025-01-01) -
An Experimental Study of Coal Gangue Pulverization for Slurry Making and a Field Test on Hulusu Coal Mine Overburden Grouting
by: Jian Li, et al.
Published: (2025-01-01) -
Research on the robustness of convolutional neural networks in image recognition
by: Dian LIN, et al.
Published: (2022-06-01)