Detection of surface defects for maize seeds based on YOLOv5-Reference-Cited by-同舟云学术

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Detection of surface defects for maize seeds based on YOLOv5

Published:2024-02 Issue: Volume:105 Page:102242
ISSN:0022-474X
Container-title:Journal of Stored Products Research
language:en
Short-container-title:Journal of Stored Products Research

Author:

Xia Yu^ORCID,Che Tianci,Meng Jingwu,Hu Jinghao,Qiao Gengle,Liu Wenbo,Kang Jie,Tang Wei

Publisher

Elsevier BV

Reference35 articles.

1. Identifying common stored product insects using automated deep learning methods;Badgujar;J. Stored Prod. Res.,2023

2. Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapur's, Otsu and Tsallis functions;Bhandari;Expert Syst. Appl.,2015

3. LeafGAN: an effective data augmentation method for practical plant disease diagnosis;Cap;IEEE Trans. Autom. Sci. Eng.,2022

4. Vigor-S, a new system for evaluating the physiological potential of maize seeds;Castan;Sci. Agric.,2018

5. Median filtering forensics based on convolutional neural networks;Chen;IEEE Signal Process. Lett.,2015

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