PlantXpert benchmark shows fine-tuned VLMs reach up to 78% accuracy on plant phenotyping but scaling gains plateau and quantitative biological reasoning remains weak.
Rady Plant Diseases Image- Text Pairs Default license (Hug- gingFace) No explicit license declared on the HuggingFace dataset card; contact author before redistribution
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A new 839K-image plant disease dataset paired with an agentic visual reasoning system that uses source-grounded symptoms raises diagnosis accuracy by 16.2 points on average and generalizes to unseen crops without retraining.
A DenseNet201 base model trained on a constructed plant leaf disease dataset outperforms baselines and enables faster, more robust transfer learning with less data than general models.
citing papers explorer
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From UAV Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping
PlantXpert benchmark shows fine-tuned VLMs reach up to 78% accuracy on plant phenotyping but scaling gains plateau and quantitative biological reasoning remains weak.
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SAGE: Scalable Agentic Grounded Evaluation for Crop Disease Diagnosis
A new 839K-image plant disease dataset paired with an agentic visual reasoning system that uses source-grounded symptoms raises diagnosis accuracy by 16.2 points on average and generalizes to unseen crops without retraining.
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Developing a Strong Pre-Trained Base Model for Plant Leaf Disease Classification
A DenseNet201 base model trained on a constructed plant leaf disease dataset outperforms baselines and enables faster, more robust transfer learning with less data than general models.