Effective feature selection based HOBS pruned- ELM model for tomato plant leaf disease classification
M. Amudha, K. Brindha · 2024
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Description
Amudha and Brindha, a two-author team, build a lightweight neural network that classifies tomato leaf diseases in real time, in a 2024 paper. Tomato farming is growing, but disease and stress cut yields. Standard image networks give good answers yet train slowly and demand heavy computing.
Their design first picks the most useful image features with a herding-inspired search method. A pruned learning machine, trimmed by a brain-surgeon style method, then does the classification with fewer connections. On a public dataset of thousands of leaf images across ten classes, the model reached high accuracy with a small file size and very fast training. The authors compare it favorably with heavier models.
Catalog record
| CREATOR | M. Amudha, K. Brindha |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 73 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |