SqueezeNet

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Description

Detects the dominant objects present in an image from a set of 1000 categories such as trees, animals, food, vehicles, people, and more. With an overall footprint of only 4.7 MB, SqueezeNet has a similar level of accuracy as AlexNet but with 50 times fewer parameters.


Specifications:

  • Format: CoreML (.mlmodel)
  • File size: 5MB

Download via Machine Learning by Apple

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