A novel method combining deep learning with the Kennard–Stone algorithm for training dataset selection for image‐based rice seed variety identification

BACKGROUND Different varieties of rice vary in planting time, stress resistance, and other characteristics. With advances in rice‐breeding technology, the number of rice varieties has increased significantly, making variety identification crucial for both trading and planting. RESULTS This study col...

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Vydáno v:	Journal of the science of food and agriculture Ročník 104; číslo 13; s. 8332 - 8342
Hlavní autoři:	Jin, Chen, Zhou, Xinyue, He, Mengyu, Li, Cheng, Cai, Zeyi, Zhou, Lei, Qi, Hengnian, Zhang, Chu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Chichester, UK John Wiley & Sons, Ltd 01.10.2024 John Wiley and Sons, Limited
Témata:	Algorithms Artificial neural networks Classification Color imagery Datasets Deep Learning Feature extraction Image enhancement Image processing Image Processing, Computer-Assisted - methods Image resolution Kennard–Stone algorithm Machine learning Neural networks Neural Networks, Computer Oryza - classification Plant breeding Planting Rice rice variety classification Seeds - chemistry training dataset selection Unsupervised learning image processing deep learning rice variety classification Kennard–Stone algorithm training dataset selection
ISSN:	0022-5142, 1097-0010, 1097-0010
On-line přístup:	Získat plný text
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