Optimized Convolution Neural Network by Swarnkar Suman (5 results)
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Taschenbuch. Condition: Neu. Optimized Convolution Neural Network (OCNN) for VBSLR | Optimized Convolution Neural Network (OCNN) for Voice-Based Sign Language Recognition: Optimization & Regularization | Suman Kumar Swarnkar (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203927931 | Verantwor…tliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2021, 2021
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Human-computer-interactions (HCI) are very helpful for current technology world. Later the trendy data policies restrict the instinctive nature & velocity of HCI use, the sign language acknowledgement framework has multiplied many s…ignificances. Completely one of a kind sign language is frequently accustomed to specific intentions and intonations or for dominant units like domestic robots. In Previous work, ICNN was once in contrast to a baseline CNN and in preceding work OCNN gain 99.96% recognition rate. The foremost centre of attention of this evaluation is to enhance the loss and execution time of ICNN model by using optimizing the preference for alternate OCNN. New model is improving configuration by applying optimizing function in bottom layer. Due to the fact it is previously acknowledged, one optimizer will never give higher accuracy for all situation. The desire for the optimizer to be created through thinking about the variability of facts and consequently the nonlinearity degree of the connection designs that happen inside the facts. As a result of the theoretical calculation isn't always sufficient to work out the easiest optimization function. 120 pp. Englisch.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Swarnkar Suman KumarDr Suman Kumar Swanrkar received a M.Tech. degree in 2015 from the Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India. He received Ph.D. (CSE) degree in 2021 from Kalinga Univer…sity, Nayaraipur, India. He has.
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2021, 2021
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Human-computer-interactions (HCI) are very helpful for current technology world. Later the trendy data policies restrict the instinctive nature & velocity of HCI use, the sign language acknowledgement framework has multiplied many signi…ficances. Completely one of a kind sign language is frequently accustomed to specific intentions and intonations or for dominant units like domestic robots. In Previous work, ICNN was once in contrast to a baseline CNN and in preceding work OCNN gain 99.96% recognition rate. The foremost centre of attention of this evaluation is to enhance the loss and execution time of ICNN model by using optimizing the preference for alternate OCNN. New model is improving configuration by applying optimizing function in bottom layer. Due to the fact it is previously acknowledged, one optimizer will never give higher accuracy for all situation. The desire for the optimizer to be created through thinking about the variability of facts and consequently the nonlinearity degree of the connection designs that happen inside the facts. As a result of the theoretical calculation isn't always sufficient to work out the easiest optimization function.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Human-computer-interactions (HCI) are very helpful for current technology world. Later the trendy data policies restrict the instinctive nature & velocity of HCI use, the sign language acknowledgement framework has multiplied many signif…icances. Completely one of a kind sign language is frequently accustomed to specific intentions and intonations or for dominant units like domestic robots. In Previous work, ICNN was once in contrast to a baseline CNN and in preceding work OCNN gain 99.96% recognition rate. The foremost centre of attention of this evaluation is to enhance the loss and execution time of ICNN model by using optimizing the preference for alternate OCNN. New model is improving configuration by applying optimizing function in bottom layer. Due to the fact it is previously acknowledged, one optimizer will never give higher accuracy for all situation. The desire for the optimizer to be created through thinking about the variability of facts and consequently the nonlinearity degree of the connection designs that happen inside the facts. As a result of the theoretical calculation isn't always sufficient to work out the easiest optimization function.
