# 224x224 resolution

Plant seedling classification model fine-tuned based on ResNet-152, achieving 77.67% accuracy on the test set

ResNet-50 is a residual network model pre-trained on ImageNet-1k, using the v1.5 architecture improvement, suitable for image classification tasks.

ConvNeXT is a pure convolutional model inspired by Vision Transformers, claiming superior performance over them. This model was trained on ImageNet-22k dataset at 224x224 resolution.

BEiT is a self-supervised learning model based on Vision Transformer (ViT), pretrained on the ImageNet-21k dataset for image classification tasks.

This Vision Transformer (ViT) model is pretrained on the ImageNet-21k dataset at 224x224 resolution, suitable for image classification tasks.

A Vision Transformer model pretrained on ImageNet-21k, featuring an extra-large architecture suitable for visual tasks like image classification.

ConvNeXT is a pure convolutional model inspired by Vision Transformers, claiming superior performance over Vision Transformers. This model was trained on the ImageNet-22k dataset at 224x224 resolution.

This Vision Transformer (ViT) model is pre-trained on the ImageNet-21k dataset and is suitable for image classification tasks.

A Vision Transformer model pretrained on the ImageNet-21k dataset, suitable for image feature extraction and downstream task fine-tuning.