AIMC Topic: Support Vector Machine

Clear Filters Showing 3151 to 3160 of 4975 articles

Introducing chaos behavior to kernel relevance vector machine (RVM) for four-class EEG classification.

PloS one
This paper addresses a chaos kernel function for the relevance vector machine (RVM) in EEG signal classification, which is an important component of Brain-Computer Interface (BCI). The novel kernel function has evolved from a chaotic system, which is...

A two-stage classification method for borehole-wall images with support vector machine.

PloS one
Analyzing geological drilling hole images acquired by Axial View Panoramic Borehole Televiewer (APBT) is a key step to explore the geological structure in a geological exploration. Conventionally, the borehole images are examined by technicians, whic...

Identification of cervical cancer using laser-induced breakdown spectroscopy coupled with principal component analysis and support vector machine.

Lasers in medical science
Cervical cancer is one of the most widespread diseases in women. Traditional cancer diagnosis is extremely complicated and relies on subjective interpretation of biopsy material. In this work, laser-induced breakdown spectroscopy (LIBS) was used in c...

Transductive Joint-Knowledge-Transfer TSK FS for Recognition of Epileptic EEG Signals.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Intelligent recognition of electroencephalogram (EEG) signals is an important means to detect seizure. Traditional methods for recognizing epileptic EEG signals are usually based on two assumptions: 1) adequate training examples are available for mod...

UAVs, Hyperspectral Remote Sensing, and Machine Learning Revolutionizing Reef Monitoring.

Sensors (Basel, Switzerland)
Recent advances in unmanned aerial system (UAS) sensed imagery, sensor quality/size, and geospatial image processing can enable UASs to rapidly and continually monitor coral reefs, to determine the type of coral and signs of coral bleaching. This pap...

Identification of research hypotheses and new knowledge from scientific literature.

BMC medical informatics and decision making
BACKGROUND: Text mining (TM) methods have been used extensively to extract relations and events from the literature. In addition, TM techniques have been used to extract various types or dimensions of interpretative information, known as Meta-Knowled...

Detecting Succinylation sites from protein sequences using ensemble support vector machine.

BMC bioinformatics
BACKGROUND: Lysine succinylation is a new kind of post-translational modification which plays a key role in protein conformation regulation and cellular function control. To understand the mechanism of succinylation profoundly, it is necessary to ide...

A support vector machine approach for AF classification from a short single-lead ECG recording.

Physiological measurement
OBJECTIVE: In this paper, a support vector machine (SVM) approach using statistical features, P wave absence, spectrum features, and length-adaptive entropy are presented to classify ECG rhythms as four types: normal rhythm, atrial fibrillation (AF),...

Time-Varying EEG Correlations Improve Automated Neonatal Seizure Detection.

International journal of neural systems
The aim of this study was to develop methods for detecting the nonstationary periodic characteristics of neonatal electroencephalographic (EEG) seizures by adapting estimates of the correlation both in the time (spike correlation; SC) and time-freque...

An in-silico method for identifying aggregation rate enhancer and mitigator mutations in proteins.

International journal of biological macromolecules
Newly synthesized polypeptides must pass stringent quality controls in cells to ensure appropriate folding and function. However, mutations, environmental stresses and aging can reduce efficiencies of these controls, leading to accumulation of protei...