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  2. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    A residual neural network (also referred to as a residual network or ResNet) [1] is a deep learning architecture in which the layers learn residual functions with reference to the layer inputs. It was developed in 2015 for image recognition , and won the ImageNet Large Scale Visual Recognition Challenge ( ILSVRC ) of that year.

  3. U-Net - Wikipedia

    en.wikipedia.org/wiki/U-Net

    The network consists of a contracting path and an expansive path (encoder-decoder), which gives it the u-shaped architecture. The contracting path is a typical convolutional network that consists of repeated application of convolutions, each followed by a rectified linear unit (ReLU) and a max pooling operation. During the contraction, the ...

  4. AlexNet - Wikipedia

    en.wikipedia.org/wiki/AlexNet

    AlexNet contains eight layers: the first five are convolutional layers, some of them followed by max-pooling layers, and the last three are fully connected layers. The network, except the last layer, is split into two copies, each run on one GPU. [1]

  5. ResNet (disambiguation) - Wikipedia

    en.wikipedia.org/wiki/ResNet_(disambiguation)

    ResNet may refer to: Residential network, a computer network provided by a university to serve residence halls; Residual flow network, in graph theory; Residual neural network, a type of artificial neural network; Residential Energy Services Network (RESNET), an organization responsible for home energy ratings

  6. Inception (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Inception_(deep_learning...

    Inception [1] is a family of convolutional neural network (CNN) for computer vision, introduced by researchers at Google in 2014 as GoogLeNet (later renamed Inception v1).). The series was historically important as an early CNN that separates the stem (data ingest), body (data processing), and head (prediction), an architectural design that persists in all modern

  7. File:ResNet block.svg - Wikipedia

    en.wikipedia.org/wiki/File:ResNet_block.svg

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses ...

  8. Timeline of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Timeline_of_artificial...

    The simplest kind of artificial neural network is the linear network. It has been known for over two centuries as the method of least squares or linear regression . It was used as a means of finding a good rough linear fit to a set of points by Adrien-Marie Legendre (1805) [ 32 ] and Carl Friedrich Gauss (1795) [ 33 ] for the prediction of ...

  9. Heterogeneous network - Wikipedia

    en.wikipedia.org/wiki/Heterogeneous_network

    A Heterogeneous wireless network (HWN) is a special case of a HetNet. Whereas a HetNet may consist of a network of computers or devices with different capabilities in terms of operating systems, hardware, protocols, etc., an HWN is a wireless network that consists of devices using different underlying radio access technology (RAT). [8]