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Stanford Car Vit Patch16
This is an image classification model based on the Vision Transformer (ViT) architecture, specifically fine-tuned on the Stanford Cars dataset for fine-grained classification of 196 car models.
Downloads 665
Release Time : 8/8/2022
Model Overview
The model is based on Google's ViT-base-patch16-224 architecture, fine-tuned on the Stanford Cars dataset to identify and classify 196 different car brands, models, and years.
Model Features
Fine-grained Classification Capability
Capable of recognizing 196 different car brands, models, and years with fine-grained classification.
ViT-based Architecture
Utilizes the Vision Transformer architecture with powerful image feature extraction capabilities.
High Accuracy
Achieves approximately 86% accuracy on the test set.
Model Capabilities
Car Image Classification
Fine-grained Category Recognition
Brand, Model, and Year Recognition
Use Cases
Automotive Industry
Used Car Identification System
Automatically identifies and classifies the brand, model, and year of used cars.
Improves used car evaluation efficiency.
Car Sales Platform
Provides automatic image classification for car sales websites.
Enhances user experience and search efficiency.
Security and Surveillance
Parking Lot Management System
Automatically identifies the model information of incoming and outgoing vehicles.
Enhances parking lot security management.
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