Enhanced Color Correction Techniques for Conveyor Belt Inspection Imagery via Unmanned Aerial Vehicles-Reference-Cited by-同舟云学术

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Enhanced Color Correction Techniques for Conveyor Belt Inspection Imagery via Unmanned Aerial Vehicles

Published:2024-04-19 Issue: Volume:53 Page:112-117
ISSN:
Container-title:2024 5th International Conference on Computer Vision, Image and Deep Learning (CVIDL)
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Author:

Chen Duo¹,Zhang Zhiqiang²,Yang Changjun²,Li Wei²,Tan Kai³,Huang Chenxuan⁴,Li Yuanyuan⁴

Affiliation:

1. CHN Energy Ningxia Coal Industry CO., LTD,Yinchuan,Ningxia,China,750000

2. CHN Energy Ningxia Coal Industry CO., LTD,Lingwu,Ningxia,China,750408

3. Chongqing Research Institute Co., LTD Jiulongpo,China Coal Technology & Engineering Group,Chongqing,China,400050

4. Robot Technology Co., LTD Nanshan,China Coal Technology & Engineering Group,Shenzhen,China,518000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10603448/10603453/10604178.pdf?arnumber=10604178

Reference14 articles.

1. A coal mine image semantic segmentation method based on fusion edge optimization;Feng;Coal Mine Safety

2. Nighttime Image Defogging Based on Multiple Light Source Model;Guo;ACTA ELECTRONICA SINICA,2017

3. DRHA-UIE: Underwater image enhancement method based on dual residual mixed attention module;Wang;ACTA ELECTRONICA SINICA,2023

4. Improving Gray World Algorithm Guided by Scene Semantics

5. A method for color correction and recognition of test paper based on perfect reflection and gray world;Wang,2018

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