Regnet X 160
RegNet image classification model trained on the ImageNet-1k dataset, designed using neural architecture search technology
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Release Time : 3/18/2022
Model Overview
RegNet is an image classification model obtained through neural architecture search (NAS) by designing search spaces, suitable for vision tasks
Model Features
Neural Architecture Search Design
Optimizes model structure step-by-step through designed search spaces for neural architecture search
Efficient Image Classification
Optimized for image classification tasks, performs well on the ImageNet dataset
Scalable Architecture
Model architecture design allows for variants of different scales (inferred)
Model Capabilities
Image Classification
Object Recognition
Use Cases
Computer Vision
General Object Recognition
Identify common object categories in images
Can recognize 1000 ImageNet categories
Animal Recognition
Identify various animal species
Successfully identified a tiger in the example
Man-Made Object Recognition
Identify everyday items such as teapots
Successfully identified a teapot in the example
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