Latest AI and machine learning research in ophthalmology for healthcare professionals.
The rapid advancements in artificial intelligence (AI), particularly the Large Language Models (LLMs), have profoundly affected our daily work and communication forms. However, it is still a challenge to deploy LLMs on resource-constrained edge devices (such as robots), due to the intensive computation requirements, heavy memory access, diverse operator types and difficulties in compilation. In ...
Migraine, a prevalent neurological disorder, has been associated with various ocular manifestations suggestive of neuronal and microvascular deficits. However, there is limited understanding of the extent to which retinal imaging may discriminate between individuals with migraines versus without migraines. In this study, we apply convolutional neural networks to color fundus photography (CFP) an...
To comprehensively assess the true visual function of clinical dry eye patients and the comprehensive impact of blinking characteristics on functional...
Domain generalizability is a crucial aspect of a deep learning model since it determines the capability of the model to perform well on data from un...
Surgery requires comprehensive medical knowledge, visual assessment skills, and procedural expertise. While recent surgical AI models have focused o...
This paper presents a low-cost eye-tracker aimed at carrying out tests based on a Visual Paired Comparison protocol for the early detection of Mild ...
Vision transformers (ViTs) have demonstrated their superior accuracy for computer vision tasks compared to convolutional neural networks (CNNs). How...
In recent years, the focus is on improving the diagnosis of diabetic retinopathy (DR) using machine learning and deep learning technologies. Researc...
Blind and low vision (BLV) developers create websites to share knowledge and showcase their work. A well-designed website can engage audiences and d...
Hyper-Spectral Imaging (HSI) is a crucial technique for analysing remote sensing data acquired from Earth observation satellites. The rich spatial a...
The end of Moore's Law and Dennard Scaling has combined with advances in agile hardware design to foster a golden age of domain-specific acceleratio...
As short-form video-sharing platforms become a significant channel for news consumption, fake news in short videos has emerged as a serious threat i...
Discriminating between Parkinson's Disease (PD) and Progressive Supranuclear Palsy (PSP) is difficult due to overlapping symptoms, especially early ...
Hallucination has been a major problem for large language models and remains a critical challenge when it comes to multimodality in which vision-lan...
Metaverse applications desire to communicate with semantically identified objects among a diverse set of cyberspace entities, such as cameras for co...
Large Vision Language Models (VLMs) extend and enhance the perceptual abilities of Large Language Models (LLMs). Despite offering new possibilities ...
The integration of artificial intelligence (AI) in healthcare, particularly in the field of dermatology, has experienced significant progress through ...
Multi-modal embeddings form the foundation for vision-language models, such as CLIP embeddings, the most widely used text-image embeddings. However,...
Vision-language models have been extensively explored across a wide range of tasks, achieving satisfactory performance; however, their application i...
Our rapid immersion into online life has made us all ill. Through the generation, personalization, and dissemination of enchanting imagery, artifici...