ResNeXt50

Imagenet classifier and general purpose backbone.

ResNeXt50 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.

Qualcomm® QCS8550
QCS8550 (Proxy)
2.50ms
Inference Time
0-2MB
Memory Usage
79NPU
Layers

Technical Details

Model checkpoint:Imagenet
Input resolution:224x224
Number of parameters:25.0M
Model size:95.4 MB

Applicable Scenarios

  • Medical Imaging
  • Anomaly Detection
  • Inventory Management

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.

Supported IoT Devices

  • QCS8550 (Proxy)

Supported IoT Chipsets

  • Qualcomm® QCS8550