AIMC Topic: Pattern Recognition, Automated

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Phenomapping for the Identification of Hypertensive Patients with the Myocardial Substrate for Heart Failure with Preserved Ejection Fraction.

Journal of cardiovascular translational research Mar 3, 2017
We sought to evaluate whether unbiased machine learning of dense phenotypic data ("phenomapping") could identify distinct hypertension subgroups that are associated with the myocardial substrate (i.e., abnormal cardiac mechanics) for heart failure wi...
Middle Aged Risk Assessment United States Hypertension Biomechanical Phenomena Male Stroke Volume Heart Failure Pattern Recognition, Automated Stress, Mechanical Echocardiography, Doppler Cluster Analysis Predictive Value of Tests Blood Pressure Phenotype Prognosis Female Adult Cross-Sectional Studies Risk Factors Aged Humans Machine Learning
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Exploiting Knowledge Composition to Improve Real-Life Hand Prosthetic Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 1, 2017
In myoelectric prosthesis control, one of the hottest topics nowadays is enforcing simultaneous and proportional (s/p) control over several degrees of freedom. This problem is particularly hard and the scientific community has so far failed to provid...
Humans Machine Learning Algorithms Computer Simulation Male Robotics Biofeedback, Psychology Hand Reproducibility of Results Young Adult Sensitivity and Specificity Movement Artificial Limbs Models, Biological Pattern Recognition, Automated
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Semi-Supervised Sparse Representation Based Classification for Face Recognition With Insufficient Labeled Samples.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Mar 1, 2017
This paper addresses the problem of face recognition when there is only few, or even only a single, labeled examples of the face that we wish to recognize. Moreover, these examples are typically corrupted by nuisance variables, both linear (i.e., add...
Face Pattern Recognition, Automated Biometric Identification Humans Algorithms Image Processing, Computer-Assisted Supervised Machine Learning Female Male
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An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

Computers in biology and medicine Feb 22, 2017
INTRODUCTION: Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture...
Photography Signal Processing, Computer-Assisted Image Interpretation, Computer-Assisted Pattern Recognition, Automated Sensitivity and Specificity Humans Diabetes Mellitus Colorimetry Algorithms Support Vector Machine Reproducibility of Results
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A Novel Graph Constructor for Semisupervised Discriminant Analysis: Combined Low-Rank and -Nearest Neighbor Graph.

Computational intelligence and neuroscience Feb 20, 2017
Semisupervised Discriminant Analysis (SDA) is a semisupervised dimensionality reduction algorithm, which can easily resolve the out-of-sample problem. Relative works usually focus on the geometric relationships of data points, which are not obvious, ...
Pattern Recognition, Automated Discriminant Analysis Humans Classification Supervised Machine Learning Algorithms Face Databases, Factual
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Interactive Exploration for Continuously Expanding Neuron Databases.

Methods (San Diego, Calif.) Feb 17, 2017
This paper proposes a novel framework to help biologists explore and analyze neurons based on retrieval of data from neuron morphological databases. In recent years, the continuously expanding neuron databases provide a rich source of information to ...
Databases, Factual Image Processing, Computer-Assisted Neurons Information Storage and Retrieval Pattern Recognition, Automated Humans Artificial Intelligence
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A weighted information criterion for multiple minor components and its adaptive extraction algorithms.

Neural networks : the official journal of the International Neural Network Society Feb 16, 2017
Minor component (MC) plays an important role in signal processing and data analysis, so it is a valuable work to develop MC extraction algorithms. Based on the concepts of weighted subspace and optimum theory, a weighted information criterion is prop...
Algorithms Computer Simulation Signal Processing, Computer-Assisted Neural Networks, Computer Pattern Recognition, Automated
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Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features.

Computational intelligence and neuroscience Feb 16, 2017
As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CN...
Humans Image Processing, Computer-Assisted Neural Networks, Computer Biomimetics Diagnostic Imaging Animals Pattern Recognition, Automated
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Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

Journal of neural engineering Feb 15, 2017
OBJECTIVE: Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a...
Signal-To-Noise Ratio Humans Discriminant Analysis Machine Learning Artifacts Reproducibility of Results Models, Neurological Pattern Recognition, Automated Sensitivity and Specificity Action Potentials Algorithms Models, Statistical Computer Simulation
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An interactive medical image segmentation framework using iterative refinement.

Computers in biology and medicine Feb 13, 2017
Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results...
Humans Machine Learning Systems Integration User-Computer Interface Algorithms Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Reproducibility of Results Pattern Recognition, Automated Sensitivity and Specificity
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