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FCN-ResNet50-Quantized

Quantized fully-convolutional network model for image segmentation.

FCN_ResNet50 is a quantized machine learning model that can segment images from the COCO dataset. It uses ResNet50 as a backbone.

14.2ms
Inference Time
5-14MB
Memory Usage
87NPU
Layers

Technical Details

Model checkpoint:COCO_WITH_VOC_LABELS_V1
Input resolution:512x512
Number of parameters:33.0M
Model size:32.2 MB

Applicable Scenarios

  • Anomaly Detection
  • Inventory Management

Licenses

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

Tags

  • quantized
    A “quantized” model can run in low or mixed precision, which can substantially reduce inference latency.

Supported IoT Devices

  • QCS6490 (Proxy)
  • QCS8250 (Proxy)
  • QCS8550 (Proxy)
  • RB3 Gen 2 (Proxy)
  • RB5 (Proxy)

Supported IoT Chipsets

  • Qualcomm® QCS6490
  • Qualcomm® QCS8250
  • Qualcomm® QCS8550