AIMC Topic: Principal Component Analysis

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Automated Parkinson's disease recognition based on statistical pooling method using acoustic features.

Medical hypotheses
Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous system and hinders people's vital activities. The majority of Parkinson's patients lose their ability to speak, write and balance. Many machine learning methods...

Input representations and classification strategies for automated human gait analysis.

Gait & posture
BACKGROUND: Quantitative gait analysis produces a vast amount of data, which can be difficult to analyze. Automated gait classification based on machine learning techniques bear the potential to support clinicians in comprehending these complex data....

Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification.

PloS one
OBJECTIVES: An extended-wavelength diffuse reflectance spectroscopy (EWDRS) technique was evaluated for its ability to differentiate between and classify different skin and tissue types in an in vivo pig model.

Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection.

Neural networks : the official journal of the International Neural Network Society
Since the principal component analysis and its variants are sensitive to outliers that affect their performance and applicability in real world, several variants have been proposed to improve the robustness. However, most of the existing methods are ...

A superpixel-driven deep learning approach for the analysis of dermatological wounds.

Computer methods and programs in biomedicine
BACKGROUND: The image-based identification of distinct tissues within dermatological wounds enhances patients' care since it requires no intrusive evaluations. This manuscript presents an approach, we named QTDU, that combines deep learning models wi...

Deep Multi-View Feature Learning for EEG-Based Epileptic Seizure Detection.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Epilepsy is a neurological illness caused by abnormal discharge of brain neurons, where epileptic seizure can lead to life-threatening emergencies. By analyzing the encephalogram (EEG) signals of patients with epilepsy, their conditions can be monito...

Research on the classification algorithm and operation parameters optimization of the system for separating non-ferrous metals from end-of-life vehicles based on machine vision.

Waste management (New York, N.Y.)
In recent years, there has been a significant increase in the number of end-of-life vehicles (ELVs) in China. The traditional methods that rely primarily on manual sorting are hard to meet the requirements anymore. To solve the low intelligence and e...

Predicting real-time 3D deformation field maps (DFM) based on volumetric cine MRI (VC-MRI) and artificial neural networks for on-board 4D target tracking: a feasibility study.

Physics in medicine and biology
To predict real-time 3D deformation field maps (DFMs) using Volumetric Cine MRI (VC-MRI) and adaptive boosting and multi-layer perceptron neural network (ADMLP-NN) for 4D target tracking. One phase of a prior 4D-MRI is set as the prior phase, MRI. Pr...

Study of the Application of Deep Convolutional Neural Networks (CNNs) in Processing Sensor Data and Biomedical Images.

Sensors (Basel, Switzerland)
The fast progress in research and development of multifunctional, distributed sensor networks has brought challenges in processing data from a large number of sensors. Using deep learning methods such as convolutional neural networks (CNN), it is pos...