Artificial Intelligence Image Recognition Method Based on Convolutional Neural Network Algorithm
IEEE Access, 2020 As an algorithm with excellent performance, convolutional neural network has been widely used in the field of image processing and achieved good results by relying on its own local receptive fields, weight sharing, pooling, and sparse connections.
Youhui Tian
doaj +1 more source
Self-Organizing Multilayered Neural Networks of Optimal Complexity [PDF]
arXiv, 2005 The principles of self-organizing the neural networks of optimal complexity is considered under the unrepresentative learning set. The method of self-organizing the multi-layered neural networks is offered and used to train the logical neural networks which were applied to the medical diagnostics.
arxiv
Postsynaptic density protein 95 (PSD-95) is transported by KIF5 to dendritic regions
Molecular Brain, 2019 Postsynaptic density protein 95 (PSD-95) is a pivotal postsynaptic scaffolding protein in excitatory neurons. Although the transport and regulation of PSD-95 in synaptic regions is well understood, dendritic transport of PSD-95 before synaptic ...
Ki-Seo Yoo +6 more
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Neural Network Processing Neural Networks: An efficient way to learn higher order functions [PDF]
arXiv, 2019 Functions are rich in meaning and can be interpreted in a variety of ways. Neural networks were proven to be capable of approximating a large class of functions[1]. In this paper, we propose a new class of neural networks called "Neural Network Processing Neural Networks" (NNPNNs), which inputs neural networks and numerical values, instead of just ...
arxiv
Building Compact and Robust Deep Neural Networks with Toeplitz Matrices [PDF]
arXiv, 2021 Deep neural networks are state-of-the-art in a wide variety of tasks, however, they exhibit important limitations which hinder their use and deployment in real-world applications. When developing and training neural networks, the accuracy should not be the only concern, neural networks must also be cost-effective and reliable.
arxiv
Static internal representation of dynamic situations reveals time compaction in human cognition
Journal of Advanced Research, 2021 Introduction: The human brain has evolved under the constraint of survival in complex dynamic situations. It makes fast and reliable decisions based on internal representations of the environment.
José Antonio Villacorta-Atienza +9 more
doaj
Application of Neural Network in Optimization of Chemical Process [PDF]
arXiv, 2021 Artificial neural network (ANN) has been widely used due to its strong nonlinear mapping ability, fault tolerance and self-learning ability. This article summarizes the development history of artificial neural networks, introduces three common neural network types, BP neural network, RBF neural network and convolutional neural network, and focuses on ...
arxiv
Variability in neural networks
eLife, 2018 Experiments on neurons in the heart system of the leech reveal why rhythmic behaviors differ between individuals.
Daniel R Kick, David J Schulz
openaire +4 more sources
A High Quality Text-To-Speech System Composed of Multiple Neural Networks
, 1998 While neural networks have been employed to handle several different text-to-speech tasks, ours is the first system to use neural networks throughout, for both linguistic and acoustic processing.
Corrigan, Gerald +5 more
core +2 more sources
Electrophysiological approaches to informing therapeutic interventions with deep brain stimulation
npj Parkinson's DiseaseNeuromodulation therapy comprises a range of non-destructive and adjustable methods for modulating neural activity using electrical stimulations, chemical agents, or mechanical interventions.
Atefeh Asadi +5 more
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