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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.
Gated recurrent units (GRUs) are a gating mechanism in recurrent neural networks, introduced in 2014 by Kyunghyun Cho et al. [1] The GRU is like a long short-term memory (LSTM) with a gating mechanism to input or forget certain features, [2] but lacks a context vector or output gate, resulting in fewer parameters than LSTM. [3]
As an example, a single 5×5 convolution can be factored into 3×3 stacked on top of another 3×3. Both has a receptive field of size 5×5. The 5×5 convolution kernel has 25 parameters, compared to just 18 in the factorized version. Thus, the 5×5 convolution is strictly more powerful than the factorized version.
The difference between a layer-3 switch and a router is the way the device is making the routing decision. Conventionally, routers use microprocessors to make forwarding decisions in software, while the switch performs only hardware-based packet switching (by specialized ASICs with the help of content-addressable memory).
A Beneš network is a rearrangeably non-blocking network derived from the clos network by initializing n = m = 2. There are (2log(N) - 1) stages, with each stage containing N/2 2*2 crossbar switches. An 8*8 Beneš network has 5 stages of switching elements, and each stage has 4 switching elements. The center three stages has two 4*4 benes network.
The network is based on a fully convolutional neural network [2] whose architecture was modified and extended to work with fewer training images and to yield more precise segmentation. Segmentation of a 512 × 512 image takes less than a second on a modern (2015) GPU using the U-Net architecture. [1] [3] [4] [5]
The switches are measured by how many stages, and how many up/down sorters and crosspoints they have. Switches often have buffers built-in for faster switching. A typical switch may have: A 2×2 and 4×4 down sorter [definition needed] Followed by an 8×8 up sorter [definition needed] Followed by a 2×2 crosspoint banyan switch network
DMLT between 2 stacked 5530 switches to an ERS 8600 switch Distributed multi-link trunking ( DMLT ) or distributed MLT is a proprietary computer networking protocol designed by Nortel Networks , and now owned by Extreme Networks , [ 8 ] used to load balance the network traffic across connections and also across multiple switches or modules in a ...