Information about Test

  1. Conference on Neural Information Processing Systems

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

  2. Caffe (software)

    CAFFE (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, originally developed at University of California, Berkeley

  3. Image scaling

    and complex artwork. Programs that use this method include waifu2x and Neural Enhance. Demonstration of conventional upscaling vs Waifu2x upscaling with

  4. SqueezeNet

    Edgar (2017-03-02). "Introducing SqueezeDet: low power fully convolutional neural network framework for autonomous driving". The Intelligence of Information

  5. Eye tracking

    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

  6. CIFAR-10

    try different algorithms to see what works. Various kinds of convolutional neural networks tend to be the best at recognizing the images in CIFAR-10. CIFAR-10

  7. WaveNet

    sounding audio. WaveNet is a type of feedforward neural network known as a deep convolutional neural network (CNN). In WaveNet, the CNN takes a raw signal

  8. Backpropagation

    training feedforward neural networks for supervised learning. Generalizations of backpropagation exist for other artificial neural networks (ANNs), and for

  9. CNN (disambiguation)

    Capone-N-Noreaga (C-N-N), a hip hop duo Cellular neural network, a parallel computing paradigm Convolutional neural network, a multilayer perceptron variation Condoms

  10. Fault detection and isolation

    constructions, 2D Convolutional neural networks can be implemented to identify faulty signals from vibration image features. Deep belief networks, Restricted