Latest AI and machine learning research in ophthalmology for healthcare professionals.
Lens Distortion Encoding System (LDES) allows for a distortion-accurate workflow, with a seamless interchange of high quality motion picture images regardless of the lens source. This system is similar in a concept to the Academy Color Encoding System (ACES), but for distortion. Presented solution is fully compatible with existing software/plug-in tools for STMapping found in popular production ...
Computational Fluid Dynamics (CFD) simulations are essential for analyzing and optimizing fluid flows in a wide range of real-world applications. These simulations involve approximating the solutions of the Navier-Stokes differential equations using numerical methods, which are highly compute- and memory-intensive due to their need for high-precision iterations. In this work, we introduce a high...
Vision is one of the essential sources through which humans acquire information. In this paper, we establish a novel framework for measuring image i...
Vision-to-audio (V2A) synthesis has broad applications in multimedia. Recent advancements of V2A methods have made it possible to generate relevant ...
Antibody generation requires the use of one or more time-consuming methods, namely animal immunization, and in vitro display technologies. However, th...
Rapid development of artificial intelligence has drastically accelerated the development of scientific discovery. Trained with large-scale observati...
Model interpretability is a key challenge that has yet to align with the advancements observed in contemporary state-of-the-art deep learning models...
This study investigates the sleep characteristics and brain activity of individuals in the gray zone of insomnia, a population that experiences slee...
Primary open-angle glaucoma (POAG) is a common ocular disease, and there is currently no effective treatment for POAG therapy. Thus, identifying some ...
Conventional computer vision models rely on very deep, feedforward networks processing whole images and trained offline with extensive labeled data....
Current neural network models of primate vision focus on replicating overall levels of behavioral accuracy, often neglecting perceptual decisions' r...
PURPOSE: The purpose of this study was to introduce SLOctolyzer: an open-source analysis toolkit for en face retinal vessels in infrared reflectance s...
Vision-language models, like CLIP (Contrastive Language Image Pretraining), are becoming increasingly popular for a wide range of multimodal retriev...
This scoping review examines the relationship between Generative AI (GenAI) and agency in education, analyzing the literature available through the ...
IMPORTANCE: Prompt and accurate diagnosis of arteritic anterior ischemic optic neuropathy (AAION) from giant cell arteritis and other systemic vasculi...
Food fraud undermines consumer trust, creates economic risk, and jeopardizes human health. Therefore, it is essential to develop efficient technologie...
Recent work has documented striking heterogeneity in the performance of state-of-the-art vision language models (VLMs), including both multimodal la...
In this work, we introduce general purpose touch representations for the increasingly accessible class of vision-based tactile sensors. Such sensors...
Understanding the genetic basis of complex traits is a longstanding challenge in the field of genomics. Genome-wide association studies (GWAS) have ...
Vision Transformers (ViTs) have outperformed traditional Convolutional Neural Networks (CNN) across various computer vision tasks. However, akin to ...