Voir la documentation de annotateImages
La acción addLayer añade una capa a un modelo de Deep Learning. Esta acción forma parte del conjunto de acciones de Deep Learning, que proporciona un superconjunto de herramientas para modelar y puntuar con redes neuronales profundas (DNN), convolucionales (CNN) y recurrentes (RNN). Es fundamental para construir arquitecturas de red capa por capa.
The `augmentImages` action is a powerful tool within the Image action set for data augmentation in computer vision tasks. It works by taking an input table of images and generating new, modified images. These transformations can include geometric changes like flipping, rotating, and cropping (creating patches), as well as color and pixel-level mutations such as color jittering, sharpening, lightening, or darkening. This process artificially expands the training dataset, which helps in building more robust and generalized deep learning models by exposing them to a wider variety of image appearances.
The addLayer action adds a layer to a deep learning model. It is part of the Deep Learning action set, which provides a comprehensive suite of tools for modeling and scoring with deep neural networks (DNN), convolutional neural networks (CNN), and recurrent neural networks (RNN). This action is fundamental in constructing the architecture of a neural network, allowing for the sequential addition and configuration of various layer types.