AIMC Topic: Photic Stimulation
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Single-pixel imaging for edge images using deep neural networks.
Applied optics
Sep 10, 2022
Edge images are often used in computer vision, cellular morphology, and surveillance cameras, and are sufficient to identify the type of object. Single-pixel imaging (SPI) is a promising technique for wide-wavelength, low-light-level measurements. Co...
Identification of cardiovascular high-risk groups from dynamic retinal vessel signals using untargeted machine learning.
Cardiovascular research
Jan 29, 2022
AIMS: Dynamic retinal vessel analysis (DVA) provides a non-invasive way to assess microvascular function in patients and potentially to improve predictions of individual cardiovascular (CV) risk. The aim of our study was to use untargeted machine lea...
Humans
Light
Vasodilation
Heart Disease Risk Factors
Cause of Death
Signal Processing, Computer-Assisted
Workflow
Risk Assessment
Venules
Cluster Analysis
Male
Photic Stimulation
Machine Learning
Renal Dialysis
Predictive Value of Tests
Cardiovascular Diseases
Retinal Vessels
Treatment Outcome
Kidney Failure, Chronic
Arterioles
Female
Middle Aged
Aged
How multisensory neurons solve causal inference.
Proceedings of the National Academy of Sciences of the United States of America
Aug 10, 2021
Sitting in a static railway carriage can produce illusory self-motion if the train on an adjoining track moves off. While our visual system registers motion, vestibular signals indicate that we are stationary. The brain is faced with a difficult chal...
Exploring and explaining properties of motion processing in biological brains using a neural network.
Journal of vision
Feb 3, 2021
Visual motion perception underpins behaviors ranging from navigation to depth perception and grasping. Our limited access to biological systems constrains our understanding of how motion is processed within the brain. Here we explore properties of mo...
Person Reidentification via Structural Deep Metric Learning.
IEEE transactions on neural networks and learning systems
Oct 1, 2019
Despite the promising progress made in recent years, person reidentification (re-ID) remains a challenging task due to the complex variations in human appearances from different camera views. This paper proposes to tackle this task by jointly learnin...
A Convolutional Neural Network for Enhancing the Detection of SSVEP in the Presence of Competing Stimuli.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Stimulus proximity has been shown to have an influence on the classification performance of a steady-state visual evoked potential based brain-computer interface (SSVEP-BCI). Multiple visual stimuli placed close to each other compete for neural repre...
Extremely Reduced Data Sets Indicate Optimal Stimulation Parameters for Classification in Brain-Computer Interfaces.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
The time between the onset of subsequent auditory or visual stimuli - also known as stimulus onset asynchrony (SOA) - determines many of the event-related potential characteristics of the resulting evoked brain signals. Specifically, the SOA value in...
Characterization of SSMVEP-based EEG signals using multiplex limited penetrable horizontal visibility graph.
Chaos (Woodbury, N.Y.)
Jul 1, 2019
The steady state motion visual evoked potential (SSMVEP)-based brain computer interface (BCI), which incorporates the motion perception capabilities of the human visual system to alleviate the negative effects caused by strong visual stimulation from...
Detecting Alzheimer's Disease from Continuous Speech Using Language Models.
Journal of Alzheimer's disease : JAD
Jan 1, 2019
BACKGROUND: Recently, many studies have been carried out to detect Alzheimer's disease (AD) from continuous speech by linguistic analysis and modeling. However, few of them utilize language models (LMs) to extract linguistic features and to investiga...
Semisupervised category learning facilitates the development of automaticity.
Attention, perception & psychophysics
Jan 1, 2019
In the human category of learning, learning is studied in a supervised, an unsupervised, or a semisupervised way. The rare human semisupervised category of learning studies all focus on early learning. However, the impact of the semisupervised catego...
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