[HTML][HTML] Big data in healthcare: management, analysis and future prospects
'Big data'is massive amounts of information that can work wonders. It has become a topic of
special interest for the past two decades because of a great potential that is hidden in it …
special interest for the past two decades because of a great potential that is hidden in it …
Quantum machine learning for chemistry and physics
Machine learning (ML) has emerged as a formidable force for identifying hidden but
pertinent patterns within a given data set with the objective of subsequent generation of …
pertinent patterns within a given data set with the objective of subsequent generation of …
A sliding window common spatial pattern for enhancing motor imagery classification in EEG-BCI
Accurate binary classification of electroencephalography (EEG) signals is a challenging task
for the development of motor imagery (MI) brain–computer interface (BCI) systems. In this …
for the development of motor imagery (MI) brain–computer interface (BCI) systems. In this …
A multi-class EEG-based BCI classification using multivariate empirical mode decomposition based filtering and Riemannian geometry
A brain-computer interface (BCI) facilitates a medium to translate the human motion
intentions using electrical brain activity signals such as electroencephalogram (EEG) into …
intentions using electrical brain activity signals such as electroencephalogram (EEG) into …
Analysis of EEG signals and its application to neuromarketing
Marketing and promotions of various consumer products through advertisement campaign is
a well known practice to increase the sales and awareness amongst the consumers. This …
a well known practice to increase the sales and awareness amongst the consumers. This …
Motor imagery EEG signals decoding by multivariate empirical wavelet transform-based framework for robust brain–computer interfaces
The robustness and computational load are the key challenges in motor imagery (MI) based
on electroencephalography (EEG) signals to decode for the development of practical brain …
on electroencephalography (EEG) signals to decode for the development of practical brain …
Quantum machine learning applications in the biomedical domain: A systematic review
Quantum technologies have become powerful tools for a wide range of application
disciplines, which tend to range from chemistry to agriculture, natural language processing …
disciplines, which tend to range from chemistry to agriculture, natural language processing …
Hybrid quantum-classical convolutional neural network model for image classification
Image classification plays an important role in remote sensing. Earth observation (EO) has
inevitably arrived in the big data era, but the high requirement on computation power has …
inevitably arrived in the big data era, but the high requirement on computation power has …
Motor imagery EEG classification based on ensemble support vector learning
Abstract Background and Objective: Brain-computer interfaces build a communication
pathway from the human brain to a computer. Motor imagery-based electroencephalogram …
pathway from the human brain to a computer. Motor imagery-based electroencephalogram …
[HTML][HTML] Implementation of artificial intelligence and machine learning-based methods in brain–computer interaction
Brain–computer interfaces are used for direct two-way communication between the human
brain and the computer. Brain signals contain valuable information about the mental state …
brain and the computer. Brain signals contain valuable information about the mental state …