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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Performance Analysis of Deep Neural Networks Using Computer Vision [PDF]
EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 2021 INTRODUCTION: In recent years, deep learning techniques have been made to outperform the earlier state-of-the-art machine learning techniques in many areas, with one of the most notable cases being computer vision.
Nidhi Sindhwani +5 more
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Automatic Programming of Cellular Automata and Artificial Neural Networks Guided by Philosophy
, 2020 Many computer models such as cellular automata and artificial neural networks have been developed and successfully applied. However, in some cases, these models might be restrictive on the possible solutions or their solutions might be difficult to ...
A Ilachinski +9 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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Hyperdrive: A Multi-Chip Systolically Scalable Binary-Weight CNN Inference Engine [PDF]
, 2019 Deep neural networks have achieved impressive results in computer vision and machine learning. Unfortunately, state-of-the-art networks are extremely compute and memory intensive which makes them unsuitable for mW-devices such as IoT end-nodes ...
Andri, Renzo +3 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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Location Dependency in Video Prediction
, 2018 Deep convolutional neural networks are used to address many computer vision problems, including video prediction. The task of video prediction requires analyzing the video frames, temporally and spatially, and constructing a model of how the environment ...
Azizi, Niloofar +2 more
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, 2020 Convolutional neural networks (CNNs) have enabled the state-of-the-art performance in many computer vision tasks. However, little effort has been devoted to establishing convolution in non-linear space.
Wang, Chen +3 more
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Efficient deep CNNs for cross-modal automated computer vision under time and space constraints [PDF]
, 2019 We present an automated computer vision architecture to handle video and image data using the same backbone networks. We show empirical results that lead us to adopt MOBILENETV2 as this backbone architecture.
Amirian, Mohammadreza +4 more
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