# Plant Disease Identification

A vision-language model fine-tuned based on the CLIP architecture, specifically designed for zero-shot classification of plant diseases

A Vision Transformer model fine-tuned on the beans dataset based on google/vit-base-patch16-224-in21k for image classification tasks

A high-precision image classification model fine-tuned on the beans dataset based on Google's ViT model

This model is a fine-tuned image classification model based on Google's ViT-base model on the beans dataset, achieving an accuracy of 98.5%.

This model is a fine-tuned image classification model based on Google's ViT-base-patch16-224-in21k on the beans dataset, achieving an accuracy of 98.5%.

An image classification model fine-tuned on the beans dataset based on Google's ViT model, achieving an accuracy of 97.74%

This model is a fine-tuned image classification model based on Google's ViT architecture on the beans dataset, achieving an accuracy of 97.74%.

This model is an image classification model fine-tuned on the beans dataset based on Google's ViT architecture, achieving an accuracy of 97.74%.

An image classification model fine-tuned on the beans dataset based on Google's ViT model, achieving an accuracy of 96.99%

An image classification model fine-tuned on a bean dataset based on Google's ViT model, achieving an accuracy of 97.74%

A high-precision image classification model fine-tuned on bean datasets based on Google's ViT model

An image classification model fine-tuned on the beans dataset based on Google's ViT base model, achieving 98.5% accuracy

A Vision Transformer model fine-tuned on an image folder dataset based on Google's ViT base model

This model is an image classification model fine-tuned on the beans dataset based on Google's ViT architecture, designed to identify the health status of legume plants.

An image classification model fine-tuned on a bean dataset based on Google's ViT model, achieving 99.25% accuracy

A vision Transformer model fine-tuned on the beans dataset based on google/vit-base-patch16-224-in21k

This model is an image classification model fine-tuned on the beans dataset based on timm/resnet18.a1_in1k, achieving an accuracy of 69.17%.

A high-precision image classification model fine-tuned on the beans dataset based on Google's ViT model

This model is based on Google's ViT architecture, fine-tuned on the beans dataset, achieving an accuracy of 98.5%.

An image classification model fine-tuned on the beans dataset based on Google's ViT model, achieving 98.5% accuracy

A plant disease image classification model based on the Swin Transformer architecture, fine-tuned on a plant disease dataset with an accuracy of 96.9%

This model is an image classification model fine-tuned on the beans dataset based on the ConvNeXt-Tiny architecture, achieving an accuracy of 96.09%.

This is a micro image classification model based on the Swin Transformer architecture, specifically fine-tuned for plant health diagnosis tasks, achieving 99.83% accuracy on the evaluation set.