Information about Test

  1. MNIST database

    aimlexchange.com/search/wiki/page/MNIST_database

    convolutional neural network best performance was 0.31 percent error rate. As of August 2018, the best performance of a single convolutional neural network

  2. Recurrent neural network

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    combined with convolutional neural networks (CNNs) improved automatic image captioning. RNNs come in many variants. Basic RNNs are a network of neuron-like

  3. U-Net

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    U-Net is a convolutional neural network that was developed for biomedical image segmentation at the Computer Science Department of the University of Freiburg

  4. DeepDream

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    created by Google engineer Alexander Mordvintsev which uses a convolutional neural network to find and enhance patterns in images via algorithmic pareidolia

  5. 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

  6. Visual temporal attention

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    video analytics tasks, such as human action recognition. In convolutional neural network-based systems, the prioritization introduced by the attention

  7. 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

  8. AlexNet

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    AlexNet is the name of a convolutional neural network, designed by Alex Krizhevsky, and published with Ilya Sutskever and Krizhevsky's PhD advisor Geoffrey

  9. 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

  10. 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

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