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ResNet50Quantized

Imagenet classifier and general purpose backbone.

ResNet50 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.

Technical Details

Model checkpoint:Imagenet
Input resolution:224x224
Number of parameters:25.5M
Model size:25.1 MB

Applicable Scenarios

  • Medical Imaging
  • Anomaly Detection
  • Inventory Management

Supported Form Factors

  • Phone
  • Tablet
  • IoT
  • XR

Licenses

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

Tags

  • backbone
    A “backbone” model is designed to extract task-agnostic representations from specific data modalities (e.g., images, text, speech). This representation can then be fine-tuned for specialized tasks.
  • quantized
    A “quantized” model can run in low or mixed precision, which can substantially reduce inference latency.

Supported Devices

  • Google Pixel 3
  • Google Pixel 3a
  • Google Pixel 3a XL
  • Google Pixel 4
  • Google Pixel 4a
  • Google Pixel 5a 5G
  • QCS8250 (Proxy)
  • QCS8550 (Proxy)
  • RB5 (Proxy)
  • SA8255 (Proxy)
  • SA8650 (Proxy)
  • SA8775 (Proxy)
  • Samsung Galaxy S21
  • Samsung Galaxy S21 Ultra
  • Samsung Galaxy S21+
  • Samsung Galaxy S22 5G
  • Samsung Galaxy S22 Ultra 5G
  • Samsung Galaxy S22+ 5G
  • Samsung Galaxy S23
  • Samsung Galaxy S23 Ultra
  • Samsung Galaxy S23+
  • Samsung Galaxy S24
  • Samsung Galaxy S24 Ultra
  • Samsung Galaxy S24+
  • Samsung Galaxy Tab S8
  • Xiaomi 12
  • Xiaomi 12 Pro

Supported Chipsets

  • Qualcomm® QCS8250
  • Qualcomm® QCS8550
  • Qualcomm® SA8255P
  • Qualcomm® SA8650P
  • Qualcomm® SA8775P
  • Snapdragon® 8 Gen 1 Mobile
  • Snapdragon® 8 Gen 2 Mobile
  • Snapdragon® 8 Gen 3 Mobile
  • Snapdragon® 888 Mobile
  • Snapdragon® X Elite