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Resnet 18 Finetuned Dogfood
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Resnet 18 Finetuned Dogfood

Developed by douwekiela
A dog food image classification model fine-tuned based on the ResNet-18 architecture, achieving 89.6% accuracy on the lewtun/dog_food dataset.
Image Classification
Transformers
Open Source License:Apache-2.0#Dog Food Classification#High Accuracy#Image Recognition
Downloads 55
Release Time : 6/26/2022

Model Overview

This model is specifically designed for image classification tasks of dog food products. By fine-tuning the pre-trained ResNet-18 model, it can accurately identify different categories of dog food products.

Model Features

High Accuracy
Achieves 89.6% classification accuracy on the test set, reliably distinguishing between different dog food products.
Lightweight Architecture
Based on the ResNet-18 architecture, it maintains good performance while having a relatively small model size.
Domain-Specific Optimization
Specifically optimized for dog food products, suitable for applications in the pet food industry.

Model Capabilities

Image Classification
Dog Food Product Recognition

Use Cases

Pet Food Industry
Automated Product Classification
Automatically identifies and classifies different brands or types of dog food products
89.6% accuracy
Inventory Management
Automatically identifies dog food product categories in warehouses through images
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