Medai Resnet50 Brain
ResNet-50 is a deep residual network developed by Microsoft Research, widely used for image classification tasks.
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Release Time : 4/7/2025
Model Overview
ResNet-50 is a classic convolutional neural network architecture that addresses the vanishing gradient problem in deep networks through residual connections, making it suitable for image classification tasks.
Model Features
Residual Connections
Effectively solves the vanishing gradient problem in deep networks through residual connections, enabling deeper and easier-to-train networks.
High Performance
Delivers outstanding performance on multiple image classification benchmark datasets, such as ImageNet.
Broad Applicability
Suitable for various image classification tasks, including but not limited to object recognition and scene classification.
Model Capabilities
Image Classification
Object Recognition
Feature Extraction
Use Cases
Computer Vision
ImageNet Classification
Performs image classification across 1,000 categories on the ImageNet dataset.
Top-1 accuracy ~76%, Top-5 accuracy ~93%.
Medical Image Analysis
Used for lesion detection and classification in medical imaging.
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