Information about Test

  1. 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

    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

    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

    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

    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

    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

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

  8. AlexNet

    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

    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

    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