Results 31 to 40 of about 852,410 (222)
Small Neural Networks can Denoise Image Textures Well: a Useful Complement to BM3D
Image Processing On Line, 2016 Recent years have seen a surge of interest in deep neural networks fueled by their successful applications in numerous image processing and computer vision tasks. However, such applications typically come with huge computational loads.
Yi-Qing Wang
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Automatic Gully Detection: Neural Networks and Computer Vision
Remote Sensing, 2020 Transition from manual (visual) interpretation to fully automated gully detection is an important task for quantitative assessment of modern gully erosion, especially when it comes to large mapping areas.
Artur M. Gafurov, Oleg P. Yermolayev
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Multi-Classifier of DDoS Attacks in Computer Networks Built on Neural Networks
Applied Sciences, 2021 The great commitment in different areas of computer science for the study of computer networks used to fulfill specific and major business tasks has generated a need for their maintenance and optimal operability. Distributed denial of service (DDoS) is a
Andrés Chartuni, José Márquez
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Guaranteed Quantization Error Computation for Neural Network Model Compression [PDF]
arXiv, 2023 Neural network model compression techniques can address the computation issue of deep neural networks on embedded devices in industrial systems. The guaranteed output error computation problem for neural network compression with quantization is addressed in this paper. A merged neural network is built from a feedforward neural network and its quantized
arxiv
Response : Computing with Neural Networks [PDF]
Science, 1987 Response: The intellectual thrust of our article (1) was to show the neurobiologist how a conceptual framework and methodology could be used to understand how a class of model neural circuits solve specific computational problems. In addition, we used examples of model circuit computation to illustrate the general problems neurobiologists face in ...
John J. Hopfield +2 more
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Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot
Освітній вимір, 2018 Semerikov S.O., Teplytsʹkyy I.O., Yechkalo YU.V. and Kiv A.E. Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot.
Сергій Семеріков +3 more
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Using spreadsheets as learning tools for computer simulation of neural networks [PDF]
SHS Web of Conferences, 2020 The article substantiates the necessity to develop training methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed.
Semerikov Serhiy +5 more
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Review of dynamic gesture recognition
Virtual Reality & Intelligent Hardware, 2021 In recent years, gesture recognition has been widely used in the fields of intelligent driving, virtual reality, and human-computer interaction. With the development of artificial intelligence, deep learning has achieved remarkable success in computer ...
Yuanyuan SHI +4 more
doaj
Deep Neural Networks in Computational Neuroscience [PDF]
, 2017 SummaryThe goal of computational neuroscience is to find mechanistic explanations of how the nervous system processes information to give rise to cognitive function and behaviour. At the heart of the field are its models, i.e. mathematical and computational descriptions of the system being studied, which map sensory stimuli to neural responses and/or ...
Kietzmann, Tim C +2 more
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Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source