Network Compression Applications
Explore model compression in end-to-end deep learning workflows that include defining requirements, data preparation, deep neural network training, compression, network testing and verification, Simulink integration, and code generation.
For a detailed overview of the compression techniques available in Deep Learning Toolbox™ Model Compression Library, see Reduce Memory Footprint of Deep Neural Networks.
Related Information
Featured Examples
Quantize Deep Learning Network for Battery State of Charge Estimation
Quantize recurrent neural network trained for battery state of charge estimation.
Compress Deep Learning Network for Battery State of Charge Estimation
Compress a neural network for predicting the state of charge of a battery using projection.
Compress Sequence Classification Network for Road Damage Detection
Compress network to meet memory requirement using pruning, projection, and quantization.
