[PDF] Top 20 EEG-based Hypo-vigilance detection using convolutional neural network
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EEG-based Hypo-vigilance detection using convolutional neural network
... the EEG signal study recorded by fourteen elec- trodes for hypo-vigilance detection by analyzing the various functionalities of the brain from the electrodes placed on the participant’s ...as ... Voir le document complet
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EEG-based Hypo-vigilance detection using convolutional neural network
... detect hypo-vigilance based on biomedical signals such as electroencephalogram (EEG), electrocardiogram (ECG), electromyogram (EMG), and electrooculogram ...on hypo-vigilance ... Voir le document complet
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Convolutional Neural Network for Multipath Detection in GNSS Receivers
... mitigation using a Support Vector Regression (SVR) ...multipath detection where the features are directly extracted from correlator ...stage using a 1D convolutional ... Voir le document complet
11
Automated analysis of foraminifera fossil records by image classification using a convolutional neural network
... reconstructions based on images have already been widely used for coccoliths ...the detection of the appearance or disappearance of species for biostrati- graphical ... Voir le document complet
21
Automatic classification of esophageal lesions in endoscopic images using a convolutional neural network
... and detection (17,18). Shichijo et al. (19) applied a deep learning AI-based diagnostic system to diagnose Helicobacter pylori infections, and Hirasawa et ...by using a CNN ... Voir le document complet
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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 ...seizures using an imaged‑EEG representation of brain ...analyzed EEG signals from two ... Voir le document complet
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Robust detection of astronomical sources using convolutional neural networks
... two convolutional neural network classifiers for detecting contaminants in astronomical ...contaminant, based on the probability that each pixel belongs to a given contaminant ... Voir le document complet
229
Craternet - A Fully Convolutional Neural Network for Lunar Crater Detection
... 4. Evaluation The evaluation of the model relies on a pixel-based error matrix from which we extract classical machine learning metrics (Re- call/sensitivity, specificity, precision, accuracy, F1-score, inter- ... Voir le document complet
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Robust parallel-gripper grasp getection using convolutional neural networks
... rated using a rule-based grasp robustness metric named Robust Ferrari ...deep neural network, dubbed Grasp-Quality CNN (GQ-CNN), to predict grasp success or ...grasp detection in a ... Voir le document complet
84
Epileptic Seizure Detection Using a Convolutional Neural Network
... experiments using real EEG dataset extracted from the Children’s Hospital Boston ...Hz EEG recordings from pediatric subjects suffering from intractable seizures [ 12 ...of EEG signal into ... Voir le document complet
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Green Function and Electromagnetic Potential for Computer Vision and Convolutional Neural Network Applications
... edge detection, feature extraction, and seamless image ...By using a single convolution based on a numerical Green’s function, the whole process is faster and straightforward to implement with ... Voir le document complet
236
Spatiotemporal analysis of EEG signal during consciousness using convolutional neural network
... experts using electroencephalography (EEG) ...studied based on machine learning ...consciousness using passive measures of brain activity has applications, and could be useful as diagnostic ... Voir le document complet
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A convolutional neural network for 250-MHz quantitative acoustic-microscopy resolution enhancement
... obtained using our 250-MHz SAM system was investigated ...reconstruction- based approach was used by minimizing the HR image total vari- ation, ...learning based approach is proposed to improve the ... Voir le document complet
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Urban Localization with Street Views using a Convolutional Neural Network for End-to-End Camera Pose Regression
... road network in order to densify the training set (gray ...and using an adapted PoseNet architecture [8] suited to our problem, we train the convnet to regress a 2D position and orientation using the ... Voir le document complet
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Automatic detection of diffusion modes within biological membranes using back-propagation neural network
... 34], detection was performed using a sliding window allowing detection of temporal changes in the mode of motion within a trajec- ...trajectories based on based on super- vised support ... Voir le document complet
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Automatic Detection of Epileptic Spikes in Intracerebral EEG with Convolutional Kernel Density Estimation
... 2.3.2 Machine Learning The past decade has seen the rise of machine learn- ing in EEG signal processing, giving birth to a rich literature. Work in this domain has focused as much on the automatic search for ... Voir le document complet
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Epileptic Spikes Detection and Visualization in Intracerebral EEG with Convolutional Kernel Density Estimation
... • ludovic.gardy@cnrs.fr • http://www.cerco.ups-tlse.fr/ - http://www.enac.fr/ References [1] N. Jrad, A. Kachenoura, I. Merlet, F. Bartolomei, A. Nica, A. Biraben, and F. Wendling. Automatic detection and ... Voir le document complet
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Visual Cognitive Driving Distraction Detection using EEG
... Nonetheless, based on eye movement x and y axis of fixation location, the distractions epoch was indeed the period of driver attending to the visual cognitive distracted secondary ... Voir le document complet
253
Image and video text recognition using convolutional neural networks
... segmentation based on the human color perception ...is based on the histogram of the lightness and the second one based on the histogram of ...used based on size constraints and Hough ... Voir le document complet
178
A convolutional neural network for 250-MHz quantitative acoustic-microscopy resolution enhancement
... obtained using our 250-MHz SAM system was investigated ...reconstruction- based approach was used by minimizing the HR image total vari- ation, ...learning based approach is proposed to improve the ... Voir le document complet
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