Integrating Shallow and Deep Features for Precision Evaluation of Corn Grain Quality: A Novel Fusion Approach
Abstract This study investigates the precision evaluation of corn grain quality, focusing on categorizing seeds into four classes: broken, discolored, pure, and silk cut. We evaluated 13 pre-trained CNN models, including AlexNet, VGG19, and ResNet, with AlexNet emerging as the top performer, achievi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-025-00889-2 |
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