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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.
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I have no idea why DenseNets are linked to Sparse network. DenseNets is a moinker used for a specific way to implement residual neural networks. If the link text had been "dense networks" it could have made sense to link to an opposite. Jeblad 20:51, 6 March 2019 (UTC)
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Recurrent neural networks (RNNs) are a class of artificial neural network commonly used for sequential data processing. Unlike feedforward neural networks, which process data in a single pass, RNNs process data across multiple time steps, making them well-adapted for modelling and processing text, speech, and time series.
Residual in the bankruptcy of insolvent businesses, moneys that are left after all assets are sold and all creditors paid, to be divided among residual claimants Residual (or balloon) in finance, a lump sum owed to the financier at the end of a loan's term; for example Balloon payment mortgage
According to Wikipedia:WikiProject Ethnic groups, there is no standard form for ethnic groups. Per Wikipedia:Naming conventions (languages), the Indonesian language should be referred to as "Indonesian" or "the Indonesian language" if necessary. "Bahasa" is not the name of the language and is simply an Indonesian word which means "language". In ...
In 2023, a controversy arose in Indonesia over the import of used Japanese rail units for use in the Commuterline network.. KAI Commuter, intending to import additional used Japanese trains to replace old rolling stock and expand the capacity of the network, failed to secure approval from a number of government bodies such as the Ministry of Industry and the Coordinating Ministry for Maritime ...