AIMC Topic: Pattern Recognition, Automated
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Classifier Subset Selection for the Stacked Generalization Method Applied to Emotion Recognition in Speech.
Sensors (Basel, Switzerland)
Dec 25, 2015
In this paper, a new supervised classification paradigm, called classifier subset selection for stacked generalization (CSS stacking), is presented to deal with speech emotion recognition. The new approach consists of an improvement of a bi-level mul...
Ultrasound Image Discrimination between Benign and Malignant Adnexal Masses Based on a Neural Network Approach.
Ultrasound in medicine & biology
Dec 20, 2015
The discrimination between benign and malignant adnexal masses in ultrasound images represents one of the most challenging problems in gynecologic practice. In the study described here, a new method for automatic discrimination of adnexal masses base...
Correlational Neural Networks.
Neural computation
Dec 14, 2015
Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based a...
Decoding intracranial EEG data with multiple kernel learning method.
Journal of neuroscience methods
Dec 12, 2015
BACKGROUND: Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced the field of neuroimaging, their app...
Signal Processing, Computer-Assisted
Feasibility Studies
Datasets as Topic
Semantics
Pattern Recognition, Automated
Rest
Neuropsychological Tests
Judgment
Humans
Machine Learning
Brain
Self Concept
Mathematical Concepts
Pattern Recognition, Visual
Memory, Episodic
Drug Resistant Epilepsy
Electrocorticography
Automatic Estimation of Osteoporotic Fracture Cases by Using Ensemble Learning Approaches.
Journal of medical systems
Dec 12, 2015
Ensemble learning methods are one of the most powerful tools for the pattern classification problems. In this paper, the effects of ensemble learning methods and some physical bone densitometry parameters on osteoporotic fracture detection were inves...
Quantifying co-cultured cell phenotypes in high-throughput using pixel-based classification.
Methods (San Diego, Calif.)
Dec 11, 2015
Biologists increasingly use co-culture systems in which two or more cell types are grown in cell culture together in order to better model cells' native microenvironments. Co-cultures are often required for cell survival or proliferation, or to maint...
Making Activity Recognition Robust against Deceptive Behavior.
PloS one
Dec 11, 2015
Healthcare services increasingly use the activity recognition technology to track the daily activities of individuals. In some cases, this is used to provide incentives. For example, some health insurance companies offer discount to customers who are...
Training and testing ERP-BCIs under different mental workload conditions.
Journal of neural engineering
Dec 10, 2015
OBJECTIVE: As one of the most popular and extensively studied paradigms of brain-computer interfaces (BCIs), event-related potential-based BCIs (ERP-BCIs) are usually built and tested in ideal laboratory settings in most existing studies, with subjec...
Pattern Recognition, Automated
Brain-Computer Interfaces
Task Performance and Analysis
Event-Related Potentials, P300
Humans
Cognition
Machine Learning
Electroencephalography
Young Adult
Communication Devices for People with Disabilities
Female
Workload
Adult
Reproducibility of Results
Word Processing
Sensitivity and Specificity
Male
A Bi-Projection Neural Network for Solving Constrained Quadratic Optimization Problems.
IEEE transactions on neural networks and learning systems
Dec 8, 2015
In this paper, a bi-projection neural network for solving a class of constrained quadratic optimization problems is proposed. It is proved that the proposed neural network is globally stable in the sense of Lyapunov, and the output trajectory of the ...
A Sequence-Based Dynamic Ensemble Learning System for Protein Ligand-Binding Site Prediction.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 3, 2015
BACKGROUND: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands...
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