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Resnet18 Catdog Classifier

Developed by hilmansw
A fine-tuned cat-dog image classification model based on ResNet-18, trained on the Kaggle Cats and Dogs dataset with an accuracy of 99.29%
Downloads 216
Release Time : 9/22/2023

Model Overview

This model is a fine-tuned version of the Microsoft ResNet-18 architecture, specifically designed for cat and dog image classification tasks. Through transfer learning and fine-tuning techniques, it achieves high accuracy on Kaggle's cat and dog classification dataset.

Model Features

High Accuracy
Achieves 99.29% classification accuracy on the test set
Transfer Learning
Fine-tuned based on the pre-trained ResNet-18 model, effectively leveraging existing feature extraction capabilities
Lightweight
The ResNet-18 architecture is relatively lightweight, suitable for deployment in resource-constrained environments

Model Capabilities

Image Classification
Cat and Dog Recognition
Transfer Learning

Use Cases

Pet Recognition
Smart Pet Album Classification
Automatically classifies cat and dog photos in user albums
Classification accuracy of 99.29%
Pet Hospital Management System
Automatically identifies pet types to simplify registration processes
Education
Machine Learning Teaching Example
Serves as a teaching case for computer vision and transfer learning
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