AIMC Topic: Pattern Recognition, Automated
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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...
The human visual system and CNNs can both support robust online translation tolerance following extreme displacements.
Journal of vision
Feb 3, 2021
Visual translation tolerance refers to our capacity to recognize objects over a wide range of different retinal locations. Although translation is perhaps the simplest spatial transform that the visual system needs to cope with, the extent to which t...
Deep Learning Detection of Sea Fan Neovascularization From Ultra-Widefield Color Fundus Photographs of Patients With Sickle Cell Hemoglobinopathy.
JAMA ophthalmology
Feb 1, 2021
IMPORTANCE: Adherence to screening for vision-threatening proliferative sickle cell retinopathy is limited among patients with sickle cell hemoglobinopathy despite guidelines recommending dilated fundus examinations beginning in childhood. An automat...
Middle Aged
Deep Learning
Predictive Value of Tests
Anemia, Sickle Cell
Adult
Cross-Sectional Studies
Male
Fluorescein Angiography
Photography
Humans
Retinal Neovascularization
Retrospective Studies
Image Interpretation, Computer-Assisted
Retinal Vessels
Female
Observer Variation
Reproducibility of Results
Pattern Recognition, Automated
Young Adult
Improved SSD network for accurate detection of optic disc and fovea and application in excyclotropia screening.
Journal of the Optical Society of America. A, Optics, image science, and vision
Jan 1, 2021
The detection of the optic disc (OD) and fovea is essential to many automatic diagnosis systems for retinal diseases. The single shot multibox detector (SSD) can generate predictions from feature maps of various resolutions, which has not been introd...
Does Artificial Intelligence Outperform Natural Intelligence in Interpreting Musculoskeletal Radiological Studies? A Systematic Review.
Clinical orthopaedics and related research
Dec 1, 2020
BACKGROUND: Machine learning (ML) is a subdomain of artificial intelligence that enables computers to abstract patterns from data without explicit programming. A myriad of impactful ML applications already exists in orthopaedics ranging from predicti...
Orthopedic Surgeons
Musculoskeletal Diseases
Pattern Recognition, Automated
Visual Perception
Musculoskeletal System
Diagnosis, Differential
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
Humans
Machine Learning
Reproducibility of Results
Clinical Competence
Ultrasonography
Magnetic Resonance Imaging
Controversial stimuli: Pitting neural networks against each other as models of human cognition.
Proceedings of the National Academy of Sciences of the United States of America
Nov 24, 2020
Distinct scientific theories can make similar predictions. To adjudicate between theories, we must design experiments for which the theories make distinct predictions. Here we consider the problem of comparing deep neural networks as models of human ...
Regularized Bagged Canonical Component Analysis for Multiclass Learning in Brain Imaging.
Neuroinformatics
Oct 1, 2020
A fundamental problem of supervised learning algorithms for brain imaging applications is that the number of features far exceeds the number of subjects. In this paper, we propose a combined feature selection and extraction approach for multiclass pr...
Decoding spectro-temporal representation for motor imagery recognition using ECoG-based brain-computer interfaces.
Journal of integrative neuroscience
Jun 30, 2020
One of the challenges in brain-computer interface systems is obtaining motor imagery recognition from brain activities. Brain-signal decoding robustness and system performance improvement during the motor imagery process are two of the essential issu...
Human gesture recognition under degraded environments using 3D-integral imaging and deep learning.
Optics express
Jun 22, 2020
In this paper, we propose a spatio-temporal human gesture recognition algorithm under degraded conditions using three-dimensional integral imaging and deep learning. The proposed algorithm leverages the advantages of integral imaging with deep learni...
Clinical applications of continual learning machine learning.
The Lancet. Digital health
Jun 1, 2020
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