# Image Recognition

A Transformer-based image classification model for identifying cats and dogs in images.

An image classification model based on ResNet-50 for identifying and classifying recyclable items.

A Bhutanese textile image classification model fine-tuned based on Google's ViT model

A Vision Transformer model fine-tuned on a flower image dataset based on Google's ViT-Base-Patch16-224 model

This is a multi-class image classification model trained using AutoTrain, designed to recognize different ethnic features.

This model is an image classification model fine-tuned on the huggan/wikiart dataset based on facebook/convnext-tiny-224, primarily used for artwork classification tasks.

A Vision Transformer model fine-tuned on a flower image dataset, based on Google's ViT model

A visual classification model fine-tuned on flower image datasets based on Google's Vision Transformer (ViT)

A vision Transformer model fine-tuned on flower image datasets based on Google's ViT model

A Vision Transformer model fine-tuned on flower image datasets based on Google's ViT model, suitable for image classification tasks

A Vision Transformer model fine-tuned on a flower image dataset based on Google's ViT model, suitable for image classification tasks

A vision object detection model fine-tuned on the beyond_words_23 dataset based on facebook/detr-resnet-50

A model fine-tuned based on facebook/deit-small-patch16-224, with no specific use case clearly stated

A fine-tuned food classification model based on google/vit-base-patch16-224-in21k, performing excellently on the evaluation set

A sketch classification model based on Microsoft's BEiT architecture, fine-tuned on an unknown dataset with an accuracy of 82.82%

A fine-tuned sketch classification model based on microsoft/beit-base-patch16-224-pt22k-ft22k, achieving 82.77% accuracy on the evaluation set

An image classification model based on PyTorch and HuggingPics, designed to recognize different types of ice cream.

A Vision Transformer model fine-tuned on a flower image dataset based on Google's ViT model

This is an image classification model based on the PyTorch framework, capable of accurately identifying and classifying hair length (long or short).

An image classification model provided by Keras, supporting multiple pre-trained architectures and suitable for common image classification tasks.

A visual classification model fine-tuned based on Google's ViT base model, suitable for domain-specific image recognition tasks

A vision classification model fine-tuned on flower image datasets based on Google's ViT model

A vision Transformer model fine-tuned on flower image datasets based on Google's ViT model

A fine-tuned Vision Transformer model based on google/vit-base-patch16-384, suitable for image classification tasks

This is an image classification model generated by HuggingPics, specifically designed to recognize specific categories of images.

A dog food image classification model fine-tuned based on the ResNet-18 architecture, achieving 89.6% accuracy on the lewtun/dog_food dataset.

Computer vision model based on ConvNeXt-Tiny architecture, suitable for image classification tasks

RegNet image classification model trained on ImageNet-1k, featuring an efficient network structure designed through neural architecture search

A PyTorch-based object detection model specifically designed to identify hot dogs in images

This is an image classification model generated by HuggingPics, specifically designed to identify hot dogs in pictures