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Information Processing Letters is a peer-reviewed scientific journal in the field of computer science, published by Elsevier. The aim of the journal is to enable fast dissemination of results in the field of information processing in the form of short papers. Submissions are limited to nine double-spaced pages.
Electronic Letters on Computer Vision and Image Analysis (usually abbreviated ELCVIA) is a peer-reviewed open-access scientific journal focusing on computer vision and image analysis (subfields of artificial intelligence) as well as image processing (a subfield of signal processing). [1]
International Journal of Computer Processing of Languages; International Journal of Computer Vision; International Journal of Cooperative Information Systems; International Journal of Creative Computing; International Journal of Data Warehousing and Mining; International Journal of e-Collaboration; International Journal of Foundations of ...
Amari's student Saito conducted the computer experiments, using a five-layered feedforward network with two learning layers. [13] In 1970, Seppo Linnainmaa published the modern form of backpropagation in his master thesis (1970). [23] [24] [13] G.M. Ostrovski et al. republished it in 1971.
Information Processing and Management is a bimonthly peer-reviewed academic journal published by Elsevier covering the field of information and computational sciences applied to management. The journal was established in 1963 as Information Storage and Retrieval , obtaining its current name in 1975.
In computer science, a multilevel feedback queue is a scheduling algorithm. Scheduling algorithms are designed to have some process running at all times to keep the central processing unit (CPU) busy. [1] The multilevel feedback queue extends standard algorithms with the following design requirements:
In deep learning, a multilayer perceptron (MLP) is a name for a modern feedforward neural network consisting of fully connected neurons with nonlinear activation functions, organized in layers, notable for being able to distinguish data that is not linearly separable.
In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views streams, or sequences of events in time, as the central input and output objects of computation.