Information about Test

  1. Convolutional Deep Belief Networks

    aimlexchange.com/search/wiki/page/Convolutional_Deep_Belief_Networks

    science, Convolutional Deep Belief Network (CDBN) is a type of deep artificial neural network that is composed of multiple layers of convolutional restricted

  2. Long short-term memory

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    artificial recurrent neural network (RNN) architecture used in the field of deep learning. Unlike standard feedforward neural networks, LSTM has feedback

  3. Waifu2x

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

  4. Q-learning

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    human levels. The DeepMind system used a deep convolutional neural network, with layers of tiled convolutional filters to mimic the effects of receptive fields

  5. Deep Image Prior

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    type of convolutional neural network used to enhance a given image with no prior training data other than the image itself. A neural network is randomly

  6. Neocognitron

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    pattern recognition tasks, and served as the inspiration for convolutional neural networks. The neocognitron was inspired by the model proposed by Hubel

  7. Ilya Sutskever

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    field of deep learning. He is the co-inventor of AlexNet, a convolutional neural network. He invented Sequence to Sequence Learning, together with Oriol

  8. Yann LeCun

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    recognition and computer vision using convolutional neural networks (CNN), and is a founding father of convolutional nets. He is also one of the main creators

  9. Conference on Neural Information Processing Systems

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    in 1986 as NIPS at the annual invitation-only Snowbird Meeting on Neural Networks for Computing organized by The California Institute of Technology and

  10. Eye tracking

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    2017 constructed a Deep Integrated Neural Network (DINN) out of a Deep Neural Network and a convolutional neural network. The goal was to use deep learning

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