Ophthalmology

Automatic glaucoma detection based on transfer induced attention network.

BACKGROUND: Glaucoma is one of the causes that leads to irreversible vision loss. Automatic glaucoma detection based on fundus images has been widely studied in recent years. However, existing methods mainly depend on a considerable amount of labeled data to train the model, which is a serious constraint for real-world glaucoma detection.

Perception and prediction of the putting distance of robot putting movements under different visual/viewing conditions.

The purpose of this paper is to examine, whether and under which conditions humans are able to predict the putting distance of a robotic device. Based on the "flash-lag effect" (FLE) it was expected that the prediction errors increase with increasing putting velocity. Furthermore, we hypothesized that the predictions are more accurate and more confident if human observers operate under full vision...

Vision-Language-Knowledge Co-Embedding for Visual Commonsense Reasoning.

Visual commonsense reasoning is an intelligent task performed to decide the most appropriate answer to a question while providing the rationale or rea...

Eye-color and Type-2 diabetes phenotype prediction from genotype data using deep learning methods.

BACKGROUND: Genotype-phenotype predictions are of great importance in genetics. These predictions can help to find genetic mutations causing variation...

A method for the automatic detection of myopia in Optos fundus images based on deep learning.

Myopia detection is significant for preventing irreversible visual impairment and diagnosing myopic retinopathy. To improve the detection efficiency a...

Predicting eyes at risk for rapid glaucoma progression based on an initial visual field test using machine learning.

OBJECTIVE: To assess whether machine learning algorithms (MLA) can predict eyes that will undergo rapid glaucoma progression based on an initial visua...

Classification Criteria for Spondyloarthritis/HLA-B27-Associated Anterior Uveitis.

PURPOSE: The purpose of this study was to determine classification criteria for spondyloarthritis/HLA-B27-associated anterior uveitis DESIGN: Machine ...

Classification Criteria for Varicella Zoster Virus Anterior Uveitis.

PURPOSE: To determine classification criteria for varicella zoster virus (VZV) anterior uveitis.

FixationNet: Forecasting Eye Fixations in Task-Oriented Virtual Environments.

Human visual attention in immersive virtual reality (VR) is key for many important applications, such as content design, gaze-contingent rendering, or...

Classification Criteria for Intermediate Uveitis, Non-Pars Planitis Type.

PURPOSE: To determine classification criteria for intermediate uveitis, non-pars planitis type (IU-NPP, also known as undifferentiated intermediate uv...

Classification Criteria for Cytomegalovirus Anterior Uveitis.

PURPOSE: To determine classification criteria for cytomegalovirus (CMV) anterior uveitis.

The Saudi Data & Artificial Intelligence Authority (SDAIA) Vision: Leading the Kingdom's Journey toward Global Leadership.

The emerging field of data and artificial intelligence (AI) and its noticeable expansion has motivated nations to transition from traditional economic...

A new deep learning method for blood vessel segmentation in retinal images based on convolutional kernels and modified U-Net model.

BACKGROUND AND OBJECTIVE: Automatic monitoring of retinal blood vessels proves very useful for the clinical assessment of ocular vascular anomalies or...

Deep Learning Ensemble Method for Classifying Glaucoma Stages Using Fundus Photographs and Convolutional Neural Networks.

: This study developed and evaluated a deep learning ensemble method to automatically grade the stages of glaucoma depending on its severity.: After c...

Limits to visual representational correspondence between convolutional neural networks and the human brain.

Convolutional neural networks (CNNs) are increasingly used to model human vision due to their high object categorization capabilities and general corr...

Artificial Neuron and Synapse Devices Based on 2D Materials.

Neuromorphic systems, which emulate neural functionalities of a human brain, are considered to be an attractive next-generation computing approach, wi...

Adopting low-shot deep learning for the detection of conjunctival melanoma using ocular surface images.

BACKGROUND AND OBJECTIVE: The purpose of the present study was to investigate low-shot deep learning models applied to conjunctival melanoma detection...

Neurophysiological brain mapping of human sleep-wake states.

OBJECTIVE: We recently proposed a spectrum-based model of the awake intracranial electroencephalogram (iEEG) (Kalamangalam et al., 2020), based on a p...

Text-Guided Neural Network Training for Image Recognition in Natural Scenes and Medicine.

Convolutional neural networks (CNNs) are widely recognized as the foundation for machine vision systems. The conventional rule of teaching CNNs to und...

Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks.

A visual object is characterized by multiple visual features, including its identity, position and size. Despite the usefulness of identity and nonide...