AIbase
EN
Home
Resnet50
R

Resnet50

Developed by leftthomas
A deep residual network model pre-trained on the ImageNet dataset for image classification tasks.
Image Classification
Transformers
#ImageNet Classification#Deep Residual Network#High-Accuracy Image Recognition
Downloads 18
Release Time : 3/2/2022

Model Overview

ResNet-50 is a deep convolutional neural network that addresses the vanishing gradient problem in deep network training through residual connections, making it suitable for image classification and other computer vision tasks.

Model Features

Residual Connections
Solves the vanishing gradient problem in deep network training through skip connections, enabling deeper and more efficient networks.
High Performance
Achieves 76.13% Top-1 accuracy and 92.86% Top-5 accuracy on the ImageNet validation set.
Transfer Learning Friendly
Can be used as a pre-trained model for fine-tuning in other computer vision tasks.

Model Capabilities

Image Classification
Feature Extraction
Transfer Learning

Use Cases

Computer Vision
General Image Classification
Classifies images into 1,000 ImageNet categories.
Top-1 accuracy 76.13%, Top-5 accuracy 92.86%
Downstream Task Fine-Tuning
Adapts to other classification tasks, image segmentation, or object detection by modifying the model's head.
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
English简体中文繁體中文にほんご
© 2025AIbase