AIMC Topic: Pattern Recognition, Automated

Clear Filters Showing 441 to 450 of 1671 articles

RFDCR: Automated brain lesion segmentation using cascaded random forests with dense conditional random fields.

NeuroImage Feb 11, 2020
Segmentation of brain lesions from magnetic resonance images (MRI) is an important step for disease diagnosis, surgical planning, radiotherapy and chemotherapy. However, due to noise, motion, and partial volume effects, automated segmentation of lesi...
Reproducibility of Results Brain Neoplasms Magnetic Resonance Imaging Humans Datasets as Topic Pattern Recognition, Automated Neuroimaging Ischemic Stroke Supervised Machine Learning Image Interpretation, Computer-Assisted
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Weighted discriminative collaborative competitive representation for robust image classification.

Neural networks : the official journal of the International Neural Network Society Feb 10, 2020
Collaborative representation-based classification (CRC) is a famous representation-based classification method in pattern recognition. Recently, many variants of CRC have been designed for many classification tasks with the good classification perfor...
Pattern Recognition, Automated Classification Neural Networks, Computer Image Processing, Computer-Assisted
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Hand Gesture Recognition Using Compact CNN Via Surface Electromyography Signals.

Sensors (Basel, Switzerland) Jan 26, 2020
By training the deep neural network model, the hidden features in Surface Electromyography(sEMG) signals can be extracted. The motion intention of the human can be predicted by analysis of sEMG. However, the models recently proposed by researchers of...
Electromyography Pattern Recognition, Automated Humans Algorithms Neural Networks, Computer Signal Processing, Computer-Assisted Reproducibility of Results Hand Gestures
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Batch Mode Active Learning on the Riemannian Manifold for Automated Scoring of Nuclear Pleomorphism in Breast Cancer.

Artificial intelligence in medicine Jan 25, 2020
Breast cancer is the most prevalent invasive type of cancer among women. The mortality rate of the disease can be reduced considerably through timely prognosis and felicitous treatment planning, by utilizing the computer aided detection and diagnosis...
Pattern Recognition, Automated Algorithms Humans Breast Neoplasms Machine Learning Image Interpretation, Computer-Assisted
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Blind method for discovering number of clusters in multidimensional datasets by regression on linkage hierarchies generated from random data.

PloS one Jan 23, 2020
Determining intrinsic number of clusters in a multidimensional dataset is a commonly encountered problem in exploratory data analysis. Unsupervised clustering algorithms often rely on specification of cluster number as an input parameter. However, th...
Humans Algorithms Cluster Analysis Regression Analysis Pattern Recognition, Automated Unsupervised Machine Learning Datasets as Topic
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A Novel Deep Learning Approach with a 3D Convolutional Ladder Network for Differential Diagnosis of Idiopathic Normal Pressure Hydrocephalus and Alzheimer's Disease.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Jan 22, 2020
PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) and Alzheimer's disease (AD) are geriatric diseases and common causes of dementia. Recently, many studies on the segmentation, disease detection, or classification of MRI using deep learning ha...
Neuroimaging Hydrocephalus, Normal Pressure Imaging, Three-Dimensional Image Processing, Computer-Assisted Magnetic Resonance Imaging Diagnosis, Differential Alzheimer Disease Pattern Recognition, Automated Case-Control Studies Diagnosis, Computer-Assisted Brain Deep Learning Female Middle Aged Reproducibility of Results Disease Progression Aged Humans Aged, 80 and over Artificial Intelligence Male
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An Optimal Electrical Impedance Tomography Drive Pattern for Human-Computer Interaction Applications.

IEEE transactions on biomedical circuits and systems Jan 20, 2020
In this article, we presented an optimal Electrical Impedance Tomography (EIT) drive pattern based on feature selection and model explanation, and proposed a portable EIT system for applications in human-computer interaction for gesture recognition a...
Pattern Recognition, Automated Tomography Electromyography Electrodes Electric Impedance Algorithms Signal Processing, Computer-Assisted Gestures Wrist Image Processing, Computer-Assisted Humans Machine Learning
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Human Body Mixed Motion Pattern Recognition Method Based on Multi-Source Feature Parameter Fusion.

Sensors (Basel, Switzerland) Jan 18, 2020
Aiming at the requirement of rapid recognition of the wearer's gait stage in the process of intelligent hybrid control of an exoskeleton, this paper studies the human body mixed motion pattern recognition technology based on multi-source feature para...
Humans Neural Networks, Computer Lower Extremity Movement Exoskeleton Device Gait Pattern Recognition, Automated Accelerometry
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Finger Gesture Spotting from Long Sequences Based on Multi-Stream Recurrent Neural Networks.

Sensors (Basel, Switzerland) Jan 18, 2020
Gesture spotting is an essential task for recognizing finger gestures used to control in-car touchless interfaces. Automated methods to achieve this task require to detect video segments where gestures are observed, to discard natural behaviors of us...
Humans Automobiles Pattern Recognition, Automated Fingers Man-Machine Systems Gestures User-Computer Interface Image Processing, Computer-Assisted Neural Networks, Computer Algorithms
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Robust adaptation regularization based on within-class scatter for domain adaptation.

Neural networks : the official journal of the International Neural Network Society Jan 17, 2020
In many practical applications, the assumption that the distributions of the data employed for training and test are identical is rarely valid, which would result in a rapid decline in performance. To address this problem, the domain adaptation strat...
Machine Learning Pattern Recognition, Automated
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