An overview of deep learning architectures that help computers detect objects, a key technology used in self-driving cars and healthcare.

Deep Neural Networks are the more computationally powerful cousins to regular neural networks. Learn exactly what DNNs are and why they are the hottest topic in machine learning research.

Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset.

Against this backdrop, HOLO has proposed a Deep Quantum Neural Network architecture that uses qubits as neurons and arbitrary unitary operations as perceptrons.

Deep learning networks mostly use neural network architectures and are hence often referred to as deep neural networks. The word “deep” refers to the number of hidden layers in the neural network.

With the use of proper neural network architecture (number of layers, number of neurons, non-linear function, etc.) along with large enough data, a deep learning network can learn any mapping from ...

There Are Many Network Designs The following diagrams from the Asimov Institute in the Netherlands reveal the variety of neural network architectures that have been created. For a neural network ...

Deepfakes are simple to make. A simple overview of the artificial intelligence (AI) behind deepfakes: Generative Adversarial Networks (GANs), Encoder-decoder pairs and First-Order Motion Models.