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mIT-CMCA: A Cross-Modal Category Alignment Framework for Robust Maize Disease Identification

2025-09-26

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<title>Abstract</title> <p>Accurate identification of maize diseases is crucial for safeguarding global food security. Traditional image-based methods often struggle with lighting variations, occlusions, and noise, which limits their robustness and generalisation ability. Multimodal approaches that integrate visual and textual information have shown promise. However, these methods frequently require manually cura...

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Literature Corpus work: 47dbc1ac-786d-515d-a5b0-022c0fe9eb40
DOI: 10.21203/rs.3.rs-7286789/v1

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