Finally, convolutional neural networks can be trained end-to-end, allowing gradient descent to simultaneously optimize all of the network’s parameters for performance and faster convergence.

Although the complexity is well justified for managing visual analytics tasks, it can limit their suitability for real-time applications like video coding, pose estimation and object recognition ...

Dr. James McCaffrey of Microsoft Research details the 'Hello World' of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset.