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Webinar: How to Achieve SOTA Accuracy & Runtime for Semantic Segmentation Models

  • Product Team
  • 2 min read

Semantic segmentation models are increasingly being used in edge applications including autonomous driving, healthcare, precision agriculture, and IoT-enabled devices.

Watch this webinar with Ofer Baratz, product manager at Deci, to learn about:

  • Best practices for training semantic segmentation models
  • How to apply transfer learning in training segmentation models
  • Open source proven recipes of common models with SOTA results
  • Performance benchmarks of real-world applications of semantic segmentation models built with Neural Architecture Search

Get started with semantic segmentation today. Go to SuperGradients on GitHub.

Train Your Segmentation Model

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					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")

model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")