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[PDF] Top 20 Epileptic Seizure Detection Using a Convolutional Neural Network

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Epileptic Seizure Detection Using a Convolutional Neural Network

Epileptic Seizure Detection Using a Convolutional Neural Network

... Convolutional Neural Network Bassem Bouaziz, Lotfi Chaari, Hadj Batatia, and Antonio Quintero-Rincón Abstract The availability of electroencephalogram (EEG) data has opened up the possibility for ... Voir le document complet

9

EEG-based Hypo-vigilance detection using convolutional neural network

EEG-based Hypo-vigilance detection using convolutional neural network

... hypo-vigilance detection by analyzing the various functionalities of the brain from the electrodes placed on the participant’s ...as Convolutional Neural Network (CNN), Recurrent CNN (R-CNN), ... Voir le document complet

11

EEG-based Hypo-vigilance detection using convolutional neural network

EEG-based Hypo-vigilance detection using convolutional neural network

... hypo-vigilance detection by analyzing the various functionalities of the brain from the electrodes placed on the participant’s ...as Convolutional Neural Network (CNN), Recurrent CNN (R-CNN), ... Voir le document complet

10

Robust parallel-gripper grasp getection using convolutional neural networks

Robust parallel-gripper grasp getection using convolutional neural networks

... cropping a patch of the image around this ...in a low-cost setting, modelling noise is a necessary step in grasp point ...gathered using a low-cost robot is very noisy because of ... Voir le document complet

84

Detection of Cardiac Arrhythmias From Varied Length Multichannel Electrocardiogram Recordings Using Deep Convolutional Neural Networks

Detection of Cardiac Arrhythmias From Varied Length Multichannel Electrocardiogram Recordings Using Deep Convolutional Neural Networks

... includes a cohort of 43101 12-lead ECG recordings with various ...design a deep one-dimensional convolu- tional neural network (CNN) called VGG-ECG, a 13-layer fully CNN for multilabel ... Voir le document complet

5

Automatic classification of esophageal lesions in endoscopic images using a convolutional neural network

Automatic classification of esophageal lesions in endoscopic images using a convolutional neural network

... the detection of EC was based on images in white light view only. Designing a universal detection system with images under more views, such as NBI and chromoendoscopy using indigo carmine, is ... Voir le document complet

11

DermaDL: Advanced Convolutional Neural Networks for Automated Melanoma Detection

DermaDL: Advanced Convolutional Neural Networks for Automated Melanoma Detection

... tional neural networks for computer-aided melanoma detection. As a result, we present the DermaDL mobile application, where dermatologists can use neural network modules for automated ... Voir le document complet

6

Automated analysis of foraminifera fossil records by image classification using a convolutional neural network

Automated analysis of foraminifera fossil records by image classification using a convolutional neural network

... likely a result of the strong dissolution affecting those intervals, as seen in the fragmen- tation ...by a micropalaeontologist and allow this method to be fully implemented for palaeoceanographic ...the ... Voir le document complet

21

Convolutional Neural Fabrics

Convolutional Neural Fabrics

... learning using standard error back-propagation ...architectures using, ...object detection, within a single non-branching network ... Voir le document complet

15

Convolutional Neural Network for Multipath Detection in GNSS Receivers

Convolutional Neural Network for Multipath Detection in GNSS Receivers

... RESEARCH A. GNSS multipath detection and mitigation Two main approaches have been proposed in the literature, frequency-domain or time domain processing ...ones using the Fast Fourier Transform (FFT) ... Voir le document complet

11

Craternet - A Fully Convolutional Neural Network for Lunar Crater Detection

Craternet - A Fully Convolutional Neural Network for Lunar Crater Detection

... 2. Data The images are provided by Narrow Angle Camera (NAC) of the Lunar Reconnaissance Orbiter. The spatial resolution of the NAC images is 0.50 m/pixel and use the panchromatic spectrum. The data are freely available ... Voir le document complet

1

Automatic seizure detection based on imaged-EEG signals through fully convolutional networks

Automatic seizure detection based on imaged-EEG signals through fully convolutional networks

... Seizure detection is a routine process in epilepsy units requiring manual intervention of well‑ trained ...detect epileptic seizures using an imaged‑EEG representation of brain ...fully ... Voir le document complet

14

Multifractal analysis for cumulant-based epileptic seizure detection in eeg time series

Multifractal analysis for cumulant-based epileptic seizure detection in eeg time series

... and epileptic patients during seizure and seizure-free periods, using publicly available data provided by the University of Bonn ...train a supervised learning algorithm to distinguish ... Voir le document complet

5

Craternet - A Fully Convolutional Neural Network for Lunar Crater Detection (presentation)

Craternet - A Fully Convolutional Neural Network for Lunar Crater Detection (presentation)

... Crater Detection Algorithms Unsupervised : • Edge detection : Canny, Robert, Sobel, Laplacian, … • Shape reconstruction : mostly using Hough transform → No need for training data but disappointing ... Voir le document complet

22

Analysis of intracerebral EEG recordings of epileptic spikes: insights from a neural network model.

Analysis of intracerebral EEG recordings of epileptic spikes: insights from a neural network model.

... beyond a certain percentage of stimulated pyramidal cells in CA1 (30%) and for increased conductances associated with glutamatergic currents, the simulated LFP could exhibit transient events ...typical ... Voir le document complet

15

An algorithm for seizure onset detection using intracranial EEG

An algorithm for seizure onset detection using intracranial EEG

... obtained using our algorithms are lower than those reported in previous work on seizure detection using IEEG, and the sensitivity was comparable ...of a real-time warning ...yielded ... Voir le document complet

18

Creating Synthetic Radar Imagery Using Convolutional Neural Networks

Creating Synthetic Radar Imagery Using Convolutional Neural Networks

... Atmospheric Technology in December, and then received this year’s Best Paper Award from the Laboratory. The Best Paper Award recognizes the authors of the most outstanding paper appearing in a peer-reviewed ... Voir le document complet

2

Automatic Detection of Epileptic Spikes in Intracerebral EEG with Convolutional Kernel Density Estimation

Automatic Detection of Epileptic Spikes in Intracerebral EEG with Convolutional Kernel Density Estimation

... being a proof of concept that density analysis of EEG can be useful, only one recording channel at a time is displayed, to avoid missing any important de- tail (but all channels are ...allowing a ... Voir le document complet

10

Urban Localization with Street Views using a Convolutional Neural Network for End-to-End Camera Pose Regression

Urban Localization with Street Views using a Convolutional Neural Network for End-to-End Camera Pose Regression

... into a set of rectilinear images similar in consti- tution to the images that will then be acquired in the online step (green ...road network in order to densify the training set (gray ...and using ... Voir le document complet

7

Epileptic Spikes Detection and Visualization in Intracerebral EEG with Convolutional Kernel Density Estimation

Epileptic Spikes Detection and Visualization in Intracerebral EEG with Convolutional Kernel Density Estimation

... drug-resistant epileptic patients can be recorded 24/7 for a duration ranging from 7 to 15 ...than a hundred channels simultane- ously, represents a huge amount of ...Interictal ... Voir le document complet

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