Regnet Y 320
RegNet image classification model trained on ImageNet-1k, featuring an efficient network structure designed via neural architecture search
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Release Time : 3/18/2022
Model Overview
RegNet is an image classification model obtained through neural architecture search by designing search spaces. Trained on the ImageNet dataset, it is suitable for vision tasks
Model Features
Neural Architecture Search Design
Automatically optimizes network structure by constructing high-dimensional search spaces and gradually narrowing the scope
Efficient Image Classification
Trained on ImageNet-1k dataset, capable of accurately identifying 1000 common object categories
Modular Design
Adopts a staged structural design with excellent scalability
Model Capabilities
Image Classification
Object Recognition
Visual Feature Extraction
Use Cases
Computer Vision
General Object Recognition
Identifies common objects in images such as animals, daily necessities, etc.
Can accurately recognize 1000 ImageNet object categories
Image Content Analysis
Analyzes the main content of images and classifies them
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