AIbase
EN
Home
Resnet50 Cifar100
R

Resnet50 Cifar100

Developed by edadaltocg
A lightweight image classification model based on the ResNet50 architecture trained on the CIFAR-100 dataset, achieving a test accuracy of 80.93%.
Image Classification EnglishOpen Source License:MIT#CIFAR100 Classification#ResNet50 Optimization#Fine-Grained Image Recognition
Downloads 56
Release Time : 2/19/2023

Model Overview

This model is a ResNet50 variant specifically optimized for the CIFAR-100 image classification task, suitable for small-scale image classification scenarios.

Model Features

Efficient Classification
Lightweight ResNet50 architecture optimized for 32x32 small-scale images
High Accuracy
Achieves 80.93% accuracy on the CIFAR-100 test set
Training Optimization
Utilizes cosine annealing learning rate scheduling and SGD optimizer

Model Capabilities

Image Classification
Small-Scale Image Processing

Use Cases

Education & Research
Image Classification Teaching
Used as a benchmark model demonstration in computer vision courses
Industrial Applications
Small Object Recognition
Suitable for low-resolution industrial inspection scenarios
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
EnglishįŽ€äŊ“中文įšéĢ”中文ãĢãģんご
Š 2025AIbase