Exploiting heterogeneity in operational neural networks by synaptic plasticity
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AbstractThe recently proposed network model, Operational Neural Networks (ONNs), can generalize the conventional Convolutional Neural Networks (CNNs) that are homogenous only with a linear neuron model. As a heterogenous network model, ONNs are based on a generalized neuron model that can encapsulateanyset of non-linear operators to boost diversity and to...
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FOS: Computer and information sciences , Computer Science - Machine Learning , Iterative methods , Biological neuron , Complex networks , Machine Learning (stat.ML) , Multi modal function , 530 , 113 , Heterogenous network , Synaptic plasticity , Machine Learning (cs.LG) , Statistics - Machine Learning , Generalized neuron , Network heterogeneity , Neural and Evolutionary Computing (cs.NE) , Mathematical operators , Training sessions , Neurons , Learning systems , Learning performance , Computer Science - Neural and Evolutionary Computing , 113 Computer and information sciences , 004 , Convolutional neural networks , Heterogeneous networks , Personnel training