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Cat Dog Classifier
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Cat Dog Classifier

Developed by MoGHenry
An image classification model fine-tuned based on the ResNet-50 architecture, specifically designed to distinguish between images of cats and dogs with an accuracy of 96.88%.
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#ResNet50 fine-tuning#Pet recognition
Downloads 58
Release Time : 1/4/2025

Model Overview

This model is a binary classification model fine-tuned from the Microsoft ResNet-50 pre-trained model, primarily used for cat and dog recognition in image classification tasks.

Model Features

High Accuracy
Achieves a classification accuracy of 96.88% on the evaluation dataset
Based on ResNet-50
Utilizes the mature ResNet-50 architecture for fine-tuning, featuring excellent feature extraction capabilities
Fast Training
Requires only 5 training epochs to achieve high performance

Model Capabilities

Image Classification
Cat and Dog Recognition
Computer Vision

Use Cases

Pet-related Applications
Automatic Pet Photo Classification
Automatically identifies and classifies user-uploaded photos of cats and dogs
Accuracy: 96.88%
Pet Social Platform Content Management
Automatically tags uploaded pet images as either cat or dog
Smart Home
Pet Recognition Access Control System
Identifies household pets to control smart access
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