Modeling of Pruning Techniques for Deep Neural Networks Simplification

Understand

Convolutional Neural Networks (CNNs) suffer from different issues, such as computational complexity and the number of parameters.

• In recent years pruning techniques are employed to reduce the number of operations and model size in CNNs.
• Different pruning methods are proposed, which are based on pruning the connections, channels, and filters.
• Various techniques and tricks accompany pruning methods, and there is not a unifying framework to model all the pruning methods.