(Choose 2 answers)
Which of the following are common reasons for using open-source implementations of ConvNets (both the model and/or weights)? Check all that apply.
A. A model trained for one computer vision task can usually be used to perform data augmentation even for a different computer vision task.
B. It is a convenient way to get working an implementation of a complex ConvNet architecture.
C. The same techniques for winning computer vision competitions, such as using multiple crops at test time,
are widely used in practical deployments (or production system deployments) of ConvNets.
D. Parameters trained for one computer vision task are often useful as pretraining for other computer vision tasks.
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