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  1. Neural architecture search

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    Neural architecture search (NAS) is a technique for automating the design of artificial neural networks (ANN), a widely used model in the field of machine

  2. Generative adversarial network

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    generator is typically a deconvolutional neural network, and the discriminator is a convolutional neural network. GANs often suffer from a "mode collapse"

  3. Siamese neural network

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    A Siamese neural network (sometimes called a twin neural network) is an artificial neural network that uses the same weights while working in tandem on

  4. Capsule neural network

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    closely mimic biological neural organization. The idea is to add structures called “capsules” to a convolutional neural network (CNN), and to reuse output

  5. Neural Style Transfer

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    appearance (style) in which it is depicted. The original paper used a convolutional neural network (CNN) VGG-19 architecture that has been pre-trained to perform

  6. Time delay neural network

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    optimizations for speech recognition. Convolutional neural network – a convolutional neural net where the convolution is performed along the time axis of

  7. Fault detection and isolation

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    constructions, 2D Convolutional neural networks can be implemented to identify faulty signals from vibration image features. Deep belief networks, Restricted

  8. Waifu2x

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    other types of photos. waifu2x was inspired by Super-Resolution Convolutional Neural Network (SRCNN). It uses Nvidia CUDA for computing, although alternative

  9. History of artificial neural networks

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    artificial neural networks (ANN) began with Warren McCulloch and Walter Pitts (1943) who created a computational model for neural networks based on algorithms

  10. Types of artificial neural networks

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    types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate

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