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LeNet
LeNet is a series of convolutional neural network structure proposed by Yann LeCun, LeCun et al. The earliest version, LeNet-1, was trained in 1989. In general, when "LeNet" is referred to without a number, it refers to LeNet-5 (1998), the most well-known version. Convolutional neural networks are a kind of Feedforward neural network, feed-forward neural network whose artificial neurons can respond to a part of the surrounding cells in the coverage range and perform well in large-scale image processing. LeNet-5 was one of the earliest convolutional neural networks and was historically important during the development of deep learning. Development history In 1988, LeCun joined the Adaptive Systems Research Department at AT&T Bell Laboratories in Holmdel, New Jersey, United States, headed by Lawrence D. Jackel. In 1988, LeCun et al. published a neural network design that recognize handwritten zip code. However, its convolutional kernels were hand-designed. In 1989, Yann LeCun e ...
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LeNet Architecture
LeNet is a series of convolutional neural network structure proposed by LeCun et al. The earliest version, LeNet-1, was trained in 1989. In general, when "LeNet" is referred to without a number, it refers to LeNet-5 (1998), the most well-known version. Convolutional neural networks are a kind of feed-forward neural network whose artificial neurons can respond to a part of the surrounding cells in the coverage range and perform well in large-scale image processing. LeNet-5 was one of the earliest convolutional neural networks and was historically important during the development of deep learning. Development history In 1988, LeCun joined the Adaptive Systems Research Department at AT&T Bell Laboratories in Holmdel, New Jersey, United States, headed by Lawrence D. Jackel. In 1988, LeCun et al. published a neural network design that recognize handwritten zip code. However, its convolutional kernels were hand-designed. In 1989, Yann LeCun et al. at Bell Labs first applied the ...
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Convolutional Neural Network
In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of artificial neural network (ANN), most commonly applied to analyze visual imagery. CNNs are also known as Shift Invariant or Space Invariant Artificial Neural Networks (SIANN), based on the shared-weight architecture of the convolution kernels or filters that slide along input features and provide translation- equivariant responses known as feature maps. Counter-intuitively, most convolutional neural networks are not invariant to translation, due to the downsampling operation they apply to the input. They have applications in image and video recognition, recommender systems, image classification, image segmentation, medical image analysis, natural language processing, brain–computer interfaces, and financial time series. CNNs are regularized versions of multilayer perceptrons. Multilayer perceptrons usually mean fully connected networks, that is, each neuron in one layer is connected to ...
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Yann LeCun - 2018 (cropped)
Yann is a French male given name, specifically, the Breton form of "Jean" (French for "John"). Notable persons with the name Yann include: __NOTOC__ In arts and entertainment *Yann Martel (born 1963), Canadian author *Yann Moix (born 1968), French author, film director and television presenter *Yann Peifer (born 1974), German disc-jockey *Yann Queffélec (born 1949), French author *Yann Tiersen (born 1970), French musician *Yann Tomita (born 1952), Japanese musician In politics and activism *Yann Fouéré (1910–2011), French activist, Breton nationalist *Yann Goulet (1914–1999), French activist, Breton nationalist *Yann Wehrling (born 1971), French politician In sports *Yann Bodiger (born 1995), French footballer *Yann Boé-Kane (born 1991), French footballer *Yann Clairay (born 1983), French racing driver *Yann Cucherat (born 1979), French gymnast *Yann Danis (born 1981), Canadian ice hockey player *Yann David (born 1988), French rugby union player *Yann Delaigue (born 197 ...
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Cheque
A cheque, or check (American English; see spelling differences) is a document that orders a bank (or credit union) to pay a specific amount of money from a person's account to the person in whose name the cheque has been issued. The person writing the cheque, known as the '' drawer'', has a transaction banking account (often called a current, cheque, chequing, checking, or share draft account) where the money is held. The drawer writes various details including the monetary amount, date, and a payee on the cheque, and signs it, ordering their bank, known as the ''drawee'', to pay the amount of money stated to the payee. Although forms of cheques have been in use since ancient times and at least since the 9th century, they became a highly popular non-cash method for making payments during the 20th century and usage of cheques peaked. By the second half of the 20th century, as cheque processing became automated, billions of cheques were issued annually; these volumes pe ...
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NCR Voyix
NCR Voyix Corporation, previously known as NCR Corporation and National Cash Register, is an American software, consulting and technology company providing several professional services and electronic products. It manufactured self-service kiosks, point-of-sale terminals, automated teller machines, check processing systems, and barcode scanners. NCR was founded in Dayton, Ohio, in 1884 and acquired by AT&T in 1991. A restructuring of AT&T in 1996 led to NCR's re-establishment on 1 January 1997, as a separate company and involved the spin-off of Lucent Technologies from AT&T. In June 2009 the company sold most of the Dayton properties and moved its headquarters to the Atlanta metropolitan area in unincorporated Gwinnett County, Georgia, near Duluth. In early January 2018, the new NCR Global Headquarters opened in Midtown Atlanta near Technology Square (adjacent to the Georgia Institute of Technology). After the strategic business review, NCR Corporation was split into two i ...
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Backpropagation
In machine learning, backpropagation (backprop, BP) is a widely used algorithm for training feedforward artificial neural networks. Generalizations of backpropagation exist for other artificial neural networks (ANNs), and for functions generally. These classes of algorithms are all referred to generically as "backpropagation". In fitting a neural network, backpropagation computes the gradient of the loss function with respect to the weights of the network for a single input–output example, and does so efficiently, unlike a naive direct computation of the gradient with respect to each weight individually. This efficiency makes it feasible to use gradient methods for training multilayer networks, updating weights to minimize loss; gradient descent, or variants such as stochastic gradient descent, are commonly used. The backpropagation algorithm works by computing the gradient of the loss function with respect to each weight by the chain rule, computing the gradient one laye ...
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R10000
The R10000, code-named "T5", is a RISC microprocessor implementation of the MIPS IV instruction set architecture (ISA) developed by MIPS Technologies, Inc. (MTI), then a division of Silicon Graphics, Inc. (SGI). The chief designers are Chris Rowen and Kenneth C. Yeager. The R10000 microarchitecture is known as ANDES, an abbreviation for Architecture with Non-sequential Dynamic Execution Scheduling. The R10000 largely replaces the R8000 in the high-end and the R4400 elsewhere. MTI was a fabless semiconductor company; the R10000 was fabricated by NEC and Toshiba. Previous fabricators of MIPS microprocessors such as Integrated Device Technology (IDT) and three others did not fabricate the R10000 as it was more expensive to do so than the R4000 and R4400. History The R10000 was introduced in January 1996 at clock frequencies of 175 MHz and 195 MHz. A 150 MHz version was introduced in the O2 product line in 1997, but discontinued shortly after due to customer ...
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SGI Origin 2000
The SGI Origin 2000 is a family of mid-range and high-end Server (computing), server computers developed and manufactured by Silicon Graphics (SGI). They were introduced in 1996 to succeed the SGI Challenge and POWER Challenge. At the time of introduction, these ran the IRIX operating system, originally version 6.4 and later, 6.5. A variant of the Origin 2000 with graphics capability is known as the SGI Onyx2, Onyx2. An entry-level variant based on the same architecture but with a different hardware implementation is known as the SGI Origin 200, Origin 200. The Origin 2000 was succeeded by the SGI Origin 3000, Origin 3000 in July 2000, and was discontinued on June 30, 2002. Models The family was announced on October 7, 1996. The project was code named ''Lego'', and also known as SN0, to indicate the first in a series of scalable node architectures, contrasting with previous symmetric multiprocessor architectures in the SGI Challenge series. The Origin 2100 is mostly the same a ...
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