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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An emulator for biologically-inspired neural networks [PDF]
, 2022 S.841-844This work presents an emulator that has been developed for real-time algorithm and architecture exploration and verification of biologically-inspired neural networks.
Kesper, M. +4 more
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Automatic Pipeline Parallel Training Framework for General-purpose Computing Devices [PDF]
Jisuanji kexueTraining large-scale neural networks usually exceeds the memory and computing capacity of a single computing node,which requires distributed training using multiple nodes.Existing distributed deep learning frameworks are mainly designed for specific ...
ZHONG Zhenyu, LIN Yongliang, WANG Haotian, LI Dongwen, SUN Yufei, ZHANG Yuzhi
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Artificial neural network approach for acute poisoning mortality prediction in emergency departments [PDF]
Clinical and Experimental Emergency Medicine, 2021 Objective The number of deaths due to acute poisoning (AP) is on the increase. It is crucial to predict AP patient mortality to identify those requiring intensive care for providing appropriate patient care as well as preserving medical resources.
Seon Yeong Park +6 more
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Harnessing Advanced Neural Architectures: A Comprehensive Approach to Stock Market Prediction Using ANN, BPNN, and GAN [PDF]
SHS Web of ConferencesThe advent of advanced neural network models has revolutionized the field of machine learning, enabling breakthroughs in various domains such as computer vision, natural language processing, and predictive analytics.
Wang Yang
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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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Deferring the learning for better generalization in radial basis neural networks [PDF]
, 2001 Proceeding of: International Conference Artificial Neural Networks — ICANN 2001. Vienna, Austria, August 21–25, 2001The level of generalization of neural networks is heavily dependent on the quality of the training data.
Galván, Inés M. +5 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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Convolutional Neural Networks and Computer Vision
Applied SciencesThe rapid development of artificial intelligence has transformed computer vision from a predominantly laboratory-oriented discipline into a broad family of deployable technologies for sensing, interpretation, decision support, and process automation [...]
Luis Usero +2 more
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A primer on deep learning and convolutional neural networks for clinicians
Insights into Imaging, 2021 Deep learning is nowadays at the forefront of artificial intelligence. More precisely, the use of convolutional neural networks has drastically improved the learning capabilities of computer vision applications, being able to directly consider raw data ...
Lara Lloret Iglesias +7 more
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