Results 21 to 30 of about 15,646 (263)
Deep Net Tree Structure for Balance of Capacity and Approximation Ability
Frontiers in Applied Mathematics and Statistics, 2019 Deep learning has been successfully used in various applications including image classification, natural language processing and game theory. The heart of deep learning is to adopt deep neural networks (deep nets for short) with certain structures to ...
Charles K. Chui +4 more
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IET Intelligent Transport Systems, 2023 Rail transit has many advantages, such as large passenger capacity, convenience, safety, and environmental protection, making it the preferred travel mode for most passengers.
Xuanrong Zhang +3 more
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Temporal Modeling of Neural Net Input/Output Behaviors: The Case of XOR
Systems, 2017 In the context of the modeling and simulation of neural nets, we formulate definitions for the behavioral realization of memoryless functions. The definitions of realization are substantively different for deterministic and stochastic systems constructed
Bernard P. Zeigler, Alexandre Muzy
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SRI3D: Two‐stream inflated 3D ConvNet based on sparse regularization for action recognition
IET Image Processing, 2023 Although most state‐of‐the‐art action recognition models have adopted a two‐stream 3D convolutional structure as a backbone network, few works have studied the impact of loss functions on action recognition models.
Zhaoqilin Yang +4 more
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Predictions models with neural nets
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2008 The contribution is oriented to basic problem trends solution of economic pointers, using neural networks. Problems include choice of the suitable model and consequently configuration of neural nets, choice computational function of neurons and the way ...
Vladimír Konečný
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Quantum speed-up in global optimization of binary neural nets
New Journal of Physics, 2021 The performance of a neural network (NN) for a given task is largely determined by the initial calibration of the network parameters. Yet, it has been shown that the calibration, also referred to as training, is generally NP-complete.
Yidong Liao +3 more
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Scientific Reports, 2022 Deep neural network (DNN) and Convolution neural network (CNN) algorithms have significantly increased the accuracies in cutting-edge large-scale image recognition and natural-language processing tasks.
Varun Bheemireddy
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TIME SERIES PREDICTION BY NEURAL NETS [PDF]
فصلنامه پژوهشهای اقتصادی ایران, 2002 Application of non-classical methods in modeling complex systems and forecasting their behavior has become as more as usual for the scientists and professionals.
Mohammad Reza Asgari Oskoei
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Neuroinformatics I: Fuzzy Neural Networks of More-Equal-Less Logic (Static)
Informatics in Education, 2004 This article analyzes the possibilities of neural nets composed of neurons - the summators of continuously varied impulse frequencies characterized by non-linearity {N}, when informational operations of fuzzy logic are performed.
Dobilas KIRVELIS, Girstaute DAGYTE
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Uncovering Neural Learning Dynamics Through Latent Mutual Information
EntropyWe study how convolutional neural networks reorganize information during learning in natural image classification tasks by tracking mutual information (MI) between inputs, intermediate representations, and labels. Across VGG-16, ResNet-18, and ResNet-50,
Arianna Issitt +4 more
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