In this part we build an image classifier starting from a pre-trained (on ImageNet) CNN under the transfer learning paradigm. Once again, we use the Deep Network Designer app to build our solution by ...

The Deep Network Designer (see figure) provides a way to use pretrained models including SqueezeNet, Inception-v3, ResNet-101, GoogLeNet, and VGG-19, as well as developing new models.

Scope For Preprocessing. Matlab gives scope for preprocessing datasets actively with domain-specific apps for audio, video, and image data. Users can visualize, check, and mend problems before ...

The new Deep Learning Toolbox, which replaces the Neural Network Toolbox, will provide engineers with a framework for designing and implementing deep neural networks. Image processing, computer vision ...

This package includes MATLAB scripts that help you design a poker player using MATLAB, Deep Learning, and Raspberry Pi. The poker-playing algorithm consists of a deep learning network that predicts ...

MATLAB provides a framework that makes deep learning easy to use for engineers and scientists. It also provides easy access to pre-trained networks developed by experts and leverages GPUs without GPU ...

Furthermore, conventional method of developing deep learning models in Python often takes considerable effort in programming ancillary functions like image input, training progress control and so on.