Deep learning is a branch of machine learning that teaches computers to do what comes naturally to humans: learn from experience. The learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. Deep learning uses convolutional neural networks (CNNs) to learn useful representations of data directly from images.
You can use MATLAB® Coder™ with Deep Learning Toolbox to generate C++ code from a trained CNN. You can deploy the generated code to an embedded platform that uses an Intel® or ARM® processor.
Deep Learning with MATLAB Coder is not supported in MATLAB Online™.
|Generate C/C++ code from MATLAB code|
|Generate code and build static library for Series or DAG Network|
|Load deep learning network model|
|Create deep learning code generation configuration objects|
|Parameters to configure deep learning code generation with the ARM Compute Library|
|Parameters to configure deep learning code generation with the Intel Math Kernel Library for Deep Neural Networks|
|Get convolutional neural network layers supported for code generation for a specific deep learning library|
Install products and configure environment for code generation for deep learning networks.
Generate code for prediction from a pretrained network.
Choose a convolutional neural network that is supported for your target processor.
object for code generation.
Generate C++ code for prediction from a deep learning network, targeting an Intel CPU.
Generate C++ code for prediction from a deep learning network, targeting an ARM processor.
Generate library or executable code on host computer for deployment on ARM hardware target.