Latest AI and machine learning research in ophthalmology for healthcare professionals.
The importance of early Alzheimer's Disease screening is becoming more apparent, given the fact that there is no way to revert the patient's status after the onset. However, the diagnostic procedure of Alzheimer's Disease involves a comprehensive analysis of cognitive tests, blood sampling, and imaging, which limits the screening of a large population in a short period. Preliminary works show that...
Predicting human gaze behavior within computer vision is integral for developing interactive systems that can anticipate user attention, address fundamental questions in cognitive science, and hold implications for fields like human-computer interaction (HCI) and augmented/virtual reality (AR/VR) systems. Despite methodologies introduced for modeling human eye gaze behavior, applying these model...
Personalized diffusion models (PDMs) have become prominent for adapting pretrained text-to-image models to generate images of specific subjects usin...
Depression, a prevalent and complex mental health issue affecting millions worldwide, presents significant challenges for detection and monitoring. ...
In the realm of deep learning, the Kolmogorov-Arnold Network (KAN) has emerged as a potential alternative to multilayer projections (MLPs). However,...
Considering the increased workload in pathology laboratories today, automated tools such as artificial intelligence models can help pathologists wit...
Recent advancements in autoregressive networks with linear complexity have driven significant research progress, demonstrating exceptional performan...
Automated retinal image medical description generation is crucial for streamlining medical diagnosis and treatment planning. Existing challenges inc...
Effectively representing medical images, especially retinal images, presents a considerable challenge due to variations in appearance, size, and con...
Histopathological analysis of Whole Slide Images (WSIs) has seen a surge in the utilization of deep learning methods, particularly Convolutional Neu...
In recent years, instruction-tuned Large Multimodal Models (LMMs) have been successful at several tasks, including image captioning and visual quest...
The quality of Virtual Reality (VR) apps is vital, particularly the rendering quality of the VR Graphical User Interface (GUI). Different from tradi...
Engineering design optimization requires an efficient combination of a 3D shape representation, an optimization algorithm, and a design performance ...
In this work, we interpret the representations of multi-object scenes in vision encoders through the lens of structured representations. Structured ...
Multi-modal learning has significantly advanced generative AI, especially in vision-language modeling. Innovations like GPT-4V and open-source proje...
In the evolving landscape of computer vision (CV) technologies, the automatic detection and interpretation of gender and emotion in images is a crit...
In recent years, artificial intelligence (AI) technologies have experienced substantial growth across various sectors, with significant strides made p...
Glaucoma is a chronic eye disease characterized by optic neuropathy, leading to irreversible vision loss. It progresses gradually, often remaining u...
We introduce a pioneering unified library that leverages depth anything, segment anything models to augment neural comprehension in language-vision ...
We introduce Optimal Eye Surgeon (OES), a framework for pruning and training deep image generator networks. Typically, untrained deep convolutional ...