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Now showing items 21-30 of 54
Progressive Operational Perceptrons with Memory
(
Elsevier B.V.
, 2020 , Article)
Generalized Operational Perceptron (GOP) was proposed to generalize the linear neuron model used in the traditional Multilayer Perceptron (MLP) by mimicking the synaptic connections of biological neurons showing nonlinear ...
Optimization on ports activation towards energy efficient data center networks
(
Springer Verlag
, 2018 , Conference Paper)
Nowadays, Internet of thing including network support (i.e. checking social media, sending emails, video conferencing) requires smart and efficient data centers to support these services. Hence, data centers become more ...
Speech Command Recognition in Computationally Constrained Environments with a Quadratic Self-Organized Operational Layer
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Automatic classification of speech commands has revolutionized human computer interactions in robotic applications. However, employed recognition models usually follow the methodology of deep learning with complicated ...
Heterogeneous Multilayer Generalized Operational Perceptron
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
The traditional multilayer perceptron (MLP) using a McCulloch-Pitts neuron model is inherently limited to a set of neuronal activities, i.e., linear weighted sum followed by nonlinear thresholding step. Previously, generalized ...
Patient-Specific Seizure Detection Using Nonlinear Dynamics and Nullclines
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Nonlinear dynamics has recently been extensively used to study epilepsy due to the complex nature of the neuronal systems. This study presents a novel method that characterizes the dynamic behavior of pediatric seizure ...
1D convolutional neural networks and applications: A survey
(
Academic Press
, 2021 , Article)
During the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations. CNNs are feed-forward Artificial Neural Networks (ANNs) with ...
Progressive Operational Perceptrons
(
Elsevier B.V.
, 2017 , Article)
There are well-known limitations and drawbacks on the performance and robustness of the feed-forward, fully-connected Artificial Neural Networks (ANNs), or the so-called Multi-Layer Perceptrons (MLPs). In this study we ...
Long-term epileptic EEG classification via 2D mapping and textural features
(
Elsevier Ltd
, 2015 , Article)
Interpretation of long-term Electroencephalography (EEG) records is a tiresome task for clinicians. This paper presents an efficient, low cost and novel approach for patient-specific classification of long-term epileptic ...
Multifrequency Polsar Image Classification Using Dual-Band 1D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
In this work, we propose a novel classification approach based on dual-band one-dimensional Convolutional Neural Networks (1D-CNNs) for classification of multifrequency polarimetric SAR (PolSAR) data. The proposed approach ...
Self-organized operational neural networks for severe image restoration problems
(
Elsevier Ltd
, 2021 , Article)
Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs. It has become the go-to methodology for tackling image ...