AIMC Topic:
Databases, Factual

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Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition.

Sensors (Basel, Switzerland) Jan 18, 2016
Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sens...
Clothing Human Activities Neural Networks, Computer Machine Learning Signal Processing, Computer-Assisted Monitoring, Ambulatory Databases, Factual Humans
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Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique.

Analytica chimica acta Jan 14, 2016
Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI pred...
Artificial Intelligence Algorithms Least-Squares Analysis Pharmaceutical Preparations Databases, Factual Drug Discovery
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Knowledge-Driven Event Extraction in Russian: Corpus-Based Linguistic Resources.

Computational intelligence and neuroscience Jan 5, 2016
Automatic event extraction form text is an important step in knowledge acquisition and knowledge base population. Manual work in development of extraction system is indispensable either in corpus annotation or in vocabularies and pattern creation for...
Models, Theoretical Natural Language Processing Russia Linguistics Information Storage and Retrieval Databases, Factual Language Humans Algorithms
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Harnessing information from injury narratives in the 'big data' era: understanding and applying machine learning for injury surveillance.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention Jan 4, 2016
OBJECTIVE: Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identi...
Population Surveillance Humans Accidents, Occupational Machine Learning Data Mining Models, Theoretical Occupational Injuries Databases, Factual
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A Modified Sparse Representation Method for Facial Expression Recognition.

Computational intelligence and neuroscience Jan 4, 2016
In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second...
Algorithms Databases, Factual Computer Simulation Humans Artificial Intelligence Pattern Recognition, Visual Pattern Recognition, Automated Facial Expression
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Multi-view L2-SVM and its multi-view core vector machine.

Neural networks : the official journal of the International Neural Network Society Dec 24, 2015
In this paper, a novel L2-SVM based classifier Multi-view L2-SVM is proposed to address multi-view classification tasks. The proposed Multi-view L2-SVM classifier does not have any bias in its objective function and hence has the flexibility like μ-S...
Databases, Factual Support Vector Machine Artificial Intelligence Algorithms
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Multiple Kernel Point Set Registration.

IEEE transactions on medical imaging Dec 22, 2015
The finite Gaussian mixture model with kernel correlation is a flexible tool that has recently received attention for point set registration. While there are many algorithms for point set registration presented in the literature, an important issue a...
Image Processing, Computer-Assisted Models, Theoretical Normal Distribution Databases, Factual Humans Four-Dimensional Computed Tomography Pulmonary Disease, Chronic Obstructive Radiography, Thoracic Machine Learning Animals Algorithms
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Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification.

Computational intelligence and neuroscience Dec 22, 2015
Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve ...
Movement Models, Neurological Databases, Factual Humans Probability Imagination Support Vector Machine Electroencephalography Algorithms Models, Statistical Brain-Computer Interfaces
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An unsupervised learning method to identify reference intervals from a clinical database.

Journal of biomedical informatics Dec 19, 2015
Reference intervals are critical for the interpretation of laboratory results. The development of reference intervals using traditional methods is time consuming and costly. An alternative approach, known as an a posteriori method, requires an expert...
Databases, Factual Unsupervised Machine Learning Medical Informatics Clinical Laboratory Techniques Reference Values Humans
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Automated identification of copepods using digital image processing and artificial neural network.

BMC bioinformatics Dec 9, 2015
BACKGROUND: Copepods are planktonic organisms that play a major role in the marine food chain. Studying the community structure and abundance of copepods in relation to the environment is essential to evaluate their contribution to mangrove trophodyn...
Neural Networks, Computer Databases, Factual Animals Automation Image Processing, Computer-Assisted Copepoda Discriminant Analysis
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