Information about Test

  1. Convolutional neural network

    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

    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

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

  4. Deep learning

    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)

    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

    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

    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

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

  9. 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

    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