AIMC Topic: Databases, Factual

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Machine learning approaches used to analyze auditory evoked responses from the human auditory brainstem: A systematic review.

Computer methods and programs in biomedicine
BACKGROUND: The application of machine learning algorithms for assessing the auditory brainstem response has gained interest over recent years with a considerable number of publications in the literature. In this systematic review, we explore how mac...

A Deep Sequence Learning Framework for Action Recognition in Small-Scale Depth Video Dataset.

Sensors (Basel, Switzerland)
Depth video sequence-based deep models for recognizing human actions are scarce compared to RGB and skeleton video sequences-based models. This scarcity limits the research advancements based on depth data, as training deep models with small-scale da...

QCforever: A Quantum Chemistry Wrapper for Everyone to Use in Black-Box Optimization.

Journal of chemical information and modeling
To obtain observable physical or molecular properties such as ionization potential and fluorescent wavelength with quantum chemical (QC) computation, multi-step computation manipulated by a human is required. Hence, automating the multi-step computat...

Multi-Task Neural Networks and Molecular Fingerprints to Enhance Compound Identification from LC-MS/MS Data.

Molecules (Basel, Switzerland)
Mass spectrometry (MS) is widely used for the identification of chemical compounds by matching the experimentally acquired mass spectrum against a database of reference spectra. However, this approach suffers from a limited coverage of the existing d...

Support vector machine embedding discriminative dictionary pair learning for pattern classification.

Neural networks : the official journal of the International Neural Network Society
Discriminative dictionary learning (DDL) aims to address pattern classification problems via learning dictionaries from training samples. Dictionary pair learning (DPL) based DDL has shown superiority as compared with most existing algorithms which o...

Individual Identification by Late Information Fusion of EmgCNN and EmgLSTM from Electromyogram Signals.

Sensors (Basel, Switzerland)
This paper is concerned with individual identification by late fusion of two-stream deep networks from Electromyogram (EMG) signals. EMG signal has more advantages on security compared to other biosignals exposed visually, such as the face, iris, and...

Database Oriented Big Data Analysis Engine Based on Deep Learning.

Computational intelligence and neuroscience
In recent years, with the development of enterprises to the Internet, the demand for cloud database is also growing, especially how to capture data quickly and efficiently through the database. In order to improve the data structure at all levels in ...

Unsupervised SAR Imagery Feature Learning with Median Filter-Based Loss Value.

Sensors (Basel, Switzerland)
The scarcity of open SAR (Synthetic Aperture Radars) imagery databases (especially the labeled ones) and sparsity of pre-trained neural networks lead to the need for heavy data generation, augmentation, or transfer learning usage. This paper describe...

Developing Graph Convolutional Networks and Mutual Information for Arrhythmic Diagnosis Based on Multichannel ECG Signals.

International journal of environmental research and public health
Cardiovascular diseases, like arrhythmia, as the leading causes of death in the world, can be automatically diagnosed using an electrocardiogram (ECG). The ECG-based diagnostic has notably resulted in reducing human errors. The main aim of this study...

Improvement of Patient Classification Using Feature Selection Applied to Bidirectional Axial Transmission.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Osteoporosis is still a worldwide problem, particularly due to associated fragility fractures. Patients at risk of fracture are currently detected using the X-Ray gold standard dual-energy X-ray absorptiometry (DXA), based on a calibrated 2-D image. ...