Information about Test

  1. Convolutional neural network

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    In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery

  2. Neural network

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    A neural network is a network or circuit of neurons, or in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus

  3. Artificial neural network

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    Artificial neural networks (ANN) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal

  4. Deep learning

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    architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields

  5. Transformer (machine learning model)

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    computation. Autoregressive convolutional neural networks can handle long-range dependencies through dilated convolutions such that the path length is

  6. 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

  7. PyTorch

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    processing units (GPU) Deep neural networks built on a tape-based autodiff system Facebook operates both PyTorch and Convolutional Architecture for Fast Feature

  8. Movidius

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    uses the Myriad 2. Vision processing unit MPSoC Coprocessor Convolutional neural network Newenham, Pamela. "Sean Mitchell and David Moloney, Movidius"

  9. Encog

    aimlexchange.com/search/wiki/page/Encog

    provided to help model and train neural networks. Encog has been in active development since 2008. ADALINE Neural Network Adaptive Resonance Theory 1 (ART1)

  10. Artificial intelligence

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    deep neural networks that contain many layers of non-linear hidden units and a very large output layer. Deep learning often uses convolutional neural networks

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