backpropagation network Search Results


theory of the backpropagation neural network  (Harcourt Brace Jovanovich)
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Harcourt Brace Jovanovich theory of the backpropagation neural network
Theory Of The Backpropagation Neural Network, supplied by Harcourt Brace Jovanovich, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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backpropagation network  (Grainger Industrial)
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Grainger Industrial backpropagation network
Backpropagation Network, supplied by Grainger Industrial, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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neural networks and backpropagation algorithms  (Yoshitomi Pharmaceutical Industries)
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Yoshitomi Pharmaceutical Industries neural networks and backpropagation algorithms
Comparison among some strategies used to infer emotions using Infrared Thermal Imaging (IRTI).
Neural Networks And Backpropagation Algorithms, supplied by Yoshitomi Pharmaceutical Industries, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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backpropagation artificial neural networks  (Eigenvector Research Inc)
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Eigenvector Research Inc backpropagation artificial neural networks
Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using <t>backpropagation</t> artificial neural networks <t>(ANNs);</t> the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).
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backpropagation neural network  (Pattern Recognition Systems (PRS) as)
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Pattern Recognition Systems (PRS) as backpropagation neural network
Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using <t>backpropagation</t> artificial neural networks <t>(ANNs);</t> the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).
Backpropagation Neural Network, supplied by Pattern Recognition Systems (PRS) as, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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mcp-regularized backpropagation neural network  (SoftMax Inc)
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SoftMax Inc mcp-regularized backpropagation neural network
Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using <t>backpropagation</t> artificial neural networks <t>(ANNs);</t> the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).
Mcp Regularized Backpropagation Neural Network, supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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time delay neural network with an autoregressive version of the backpropagation algorithm  (New Brunswick Scientific)
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New Brunswick Scientific time delay neural network with an autoregressive version of the backpropagation algorithm
Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using <t>backpropagation</t> artificial neural networks <t>(ANNs);</t> the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).
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backpropagation neural network  (Toshniwal Hyvac)
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Toshniwal Hyvac backpropagation neural network
Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using <t>backpropagation</t> artificial neural networks <t>(ANNs);</t> the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).
Backpropagation Neural Network, supplied by Toshniwal Hyvac, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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backpropagation and radial basis function network  (NeuralWare Inc)
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Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using <t>backpropagation</t> artificial neural networks <t>(ANNs);</t> the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).
Backpropagation And Radial Basis Function Network, supplied by NeuralWare Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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backpropagation neural network learning algorithm  (Kodak)
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Kodak backpropagation neural network learning algorithm
Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using <t>backpropagation</t> artificial neural networks <t>(ANNs);</t> the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).
Backpropagation Neural Network Learning Algorithm, supplied by Kodak, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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artificial neural network models  (National Research Council Canada)
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National Research Council Canada artificial neural network models
Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using <t>backpropagation</t> artificial neural networks <t>(ANNs);</t> the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).
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2-layer backpropagation neural network neuralware, inc., pittsburgh, pa  (NeuralWare Inc)
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NeuralWare Inc 2-layer backpropagation neural network neuralware, inc., pittsburgh, pa
Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using <t>backpropagation</t> artificial neural networks <t>(ANNs);</t> the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).
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Image Search Results


Comparison among some strategies used to infer emotions using Infrared Thermal Imaging (IRTI).

Journal: Sensors (Basel, Switzerland)

Article Title: Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction

doi: 10.3390/s19132844

Figure Lengend Snippet: Comparison among some strategies used to infer emotions using Infrared Thermal Imaging (IRTI).

Article Snippet: Yoshitomi et al. [ ] , 1 , N/A , 90.0 , Neural Networks and Backpropagation algorithms that recognize emotions of happiness, surprise and neutral state..

Techniques: Comparison, Imaging, Extraction, Plasmid Preparation, Expressing

Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using backpropagation artificial neural networks (ANNs); the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).

Journal: Diagnostics

Article Title: Investigation of Long-Term CD4+ T Cell Receptor Repertoire Changes Following SARS-CoV-2 Infection in Patients with Different Severities of Disease

doi: 10.3390/diagnostics14202330

Figure Lengend Snippet: Exploratory analysis by PCA comparing COVID-19 patients (all severity groups; inclusive of all collected timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Key loadings on PC2. ( e ) Classification modelling using backpropagation artificial neural networks (ANNs); the model shows good separation for MA and IP critical, and lower performance is noted for IP severe followed by IP moderate (correct responses shaded in yellow).

Article Snippet: Multivariate analyses were performed by means of principal component analysis (PCA) and backpropagation artificial neural networks (ANNs) within the MATLAB environment using the PLS Toolbox version 7.9.3 (Eigenvector Research, Inc., Manson, WA, USA) and the Classification Toolbox by Ballabio and Consonni [ ].

Techniques:

Exploratory analysis by PCA comparing COVID-19 IP severity groups (all timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Good clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Classification modelling using backpropagation artificial neural networks (ANNs); good classification between IP severity groups can be obtained (correct responses shaded in yellow), thus, given the TCR VB family CD4+ percentage, the model can predict if the patient is moderate, severe, or critical. ( e ) ROC analysis curves; performance characteristics indicate outstanding discrimination for classification of moderate and critical disease IPs, and excellent discrimination for severe disease IPs, sensitivity (blue), specificity (red).

Journal: Diagnostics

Article Title: Investigation of Long-Term CD4+ T Cell Receptor Repertoire Changes Following SARS-CoV-2 Infection in Patients with Different Severities of Disease

doi: 10.3390/diagnostics14202330

Figure Lengend Snippet: Exploratory analysis by PCA comparing COVID-19 IP severity groups (all timepoints). ( a ) ANOVA test for each TCR vb family ( p < 0.05 is considered statistically significant [circled]). ( b ) PCA performed using the TCR vb families with p < 0.05. Good clustering separation between the groups can be observed. ( c ) Key loadings (features) on PC1. ( d ) Classification modelling using backpropagation artificial neural networks (ANNs); good classification between IP severity groups can be obtained (correct responses shaded in yellow), thus, given the TCR VB family CD4+ percentage, the model can predict if the patient is moderate, severe, or critical. ( e ) ROC analysis curves; performance characteristics indicate outstanding discrimination for classification of moderate and critical disease IPs, and excellent discrimination for severe disease IPs, sensitivity (blue), specificity (red).

Article Snippet: Multivariate analyses were performed by means of principal component analysis (PCA) and backpropagation artificial neural networks (ANNs) within the MATLAB environment using the PLS Toolbox version 7.9.3 (Eigenvector Research, Inc., Manson, WA, USA) and the Classification Toolbox by Ballabio and Consonni [ ].

Techniques: