# High-precision Image Recognition

A pet breed classification model fine-tuned based on Google Vision Transformer (ViT), achieving 94.45% accuracy on the Oxford-IIIT Pets dataset

A plant disease image classification model based on MobileNetV2 architecture, achieving 97.77% accuracy in image classification tasks

Fine-tuned based on Google's ViT model for accommodation room image classification, achieving 87.5% accuracy on the validation set

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

Plant seedling classification model trained on a balanced dataset, achieving 94.67% accuracy on the test set

A binary classification model based on ViT architecture for distinguishing between car and motorcycle images, achieving 99.38% accuracy

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

A snack image classification model based on the Swin Transformer architecture, achieving an accuracy of 94.55% after fine-tuning on a snack dataset

This is an image classification model based on the DeiT architecture, specifically designed for rock particle classification tasks.