Enhancing rice seed purity recognition accuracy based on optimal feature selection
This study proposes a robust and accurate approach for classifying rice variety purity to meet stringent agricultural standards. To achieve this, we construct a comprehensive dataset by leveraging diverse types of features encompassing morphological properties, overall image structure, texture infor...
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Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2025-05-01
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Series: | Ecological Informatics |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1574954125000536 |
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