Progressive feature enrichment and ensemble learning for enhanced rice seed purity classification
This study introduces an effective method for classifying rice seed purity varieties, addressing the challenge of identifying mixed seeds in real-world scenarios. Initially, conventional feature extraction methods such as Gray Level Co-occurrence Matrix (GLCM), Scale-Invariant Feature Transform (SIF...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-10-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016825009184 |
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