An improved 3D-SwinT-CNN network to evaluate the fermentation degree of black tea-Reference-Cited by-同舟云学术

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An improved 3D-SwinT-CNN network to evaluate the fermentation degree of black tea

Published:2025-01 Issue: Volume:167 Page:110756
ISSN:0956-7135
Container-title:Food Control
language:en
Short-container-title:Food Control

Author:

Zhu Fengle,Wang Jian,Zhang Yuqian,Shi Jiang^ORCID,He Mengzhu,Zhao Zhangfeng

Publisher

Elsevier BV

Reference44 articles.

1. Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance;Aasen;ISPRS Journal of Photogrammetry and Remote Sensing,2015

2. Potential of deep learning and snapshot hyperspectral imaging for classification of species in meat;Al-Sarayreh;Food Control,2020

3. Hyperspectral imaging technology coupled with human sensory information to evaluate the fermentation degree of black tea;An;Sensors and Actuators B: Chemical,2022

4. Monitoring the major taste components during black tea fermentation using multielement fusion information in decision level;An;Food Chemistry X,2023

5. End-to-end 3D CNN for plot-scale soybean yield prediction using multitemporal UAV-based RGB images;Bhadra;Precision Agriculture,2024

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