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DeepLabV3-ResNet50

Deep Convolutional Neural Network model for semantic segmentation.

DeepLabV3 is designed for semantic segmentation at multiple scales, trained on the COCO dataset. It uses ResNet50 as a backbone.

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Technical Details

Model checkpoint:COCO_WITH_VOC_LABELS_V1
Input resolution:513x513
Number of parameters:39.6M
Model size:151 MB
Number of output classes:21

Applicable Scenarios

  • Anomaly Detection
  • Inventory Management

Licenses

Source Model:BSD-3-CLAUSE
Deployable Model:AI Model Hub License

Supported Compute Chipsets

  • Snapdragon® X Elite