Latest AI and machine learning research in ophthalmology for healthcare professionals.
Smart contact lenses are at the forefront of integrating microelectronics, biomedical engineering, and optics into wearable technologies. This work addresses a key obstacle in their development: achieving autonomous power without compromising safety or miniaturization. We examine energy harvesting strategies using intrinsic ocular sources-particularly tear salinity and eyelid motion-to enable su...
Large-scale pretrained vision backbones have transformed computer vision by providing powerful feature extractors that enable various downstream tasks, including training-free approaches like visual prompting for semantic segmentation. Despite their success in generic scenarios, these models often fall short when applied to specialized technical domains where the visual features differ significa...
Vision-Language Models (VLMs) are essential for multimodal tasks, especially compositional reasoning (CR) tasks, which require distinguishing fine-g...
Vision Language Models (VLMs) employed for visual question-answering (VQA) in autonomous driving often require substantial computational resources t...
After a renaissance phase in which researchers revisited the message-passing paradigm through the lens of deep learning, the graph machine learning ...
Large Vision-Language Models (LVLMs) have achieved significant success in multimodal tasks, with multimodal chain-of-thought (MCoT) further enhancin...
Recently, Vision-Language foundation models like CLIP and ALIGN, which are pre-trained on large-scale data have shown remarkable zero-shot generaliz...
Vision language models (VLMs) have achieved impressive performance across a variety of computer vision tasks. However, the multimodal reasoning capa...
The extraction of visual features is an essential step in Visual Question Answering (VQA). Building a good visual representation of the analyzed sce...
Vision-Language Models (VLMs) have demonstrated impressive capabilities in understanding visual content, but their reliability in safety-critical co...
Accurately estimating the informativeness of individual samples in a dataset is an important objective in deep learning, as it can guide sample sele...
Accurate segmentation of anatomical structures in volumetric medical images is crucial for clinical applications, including disease monitoring and c...
Recently, large vision-language models (LVLMs) have emerged as the preferred tools for judging text-image alignment, yet their robustness along the ...
Artificial intelligence (AI) has developed greatly and is now at the centre of technological advancements. Current and recent military conflicts have ...
The rapid advancement of implantable biomedical materials necessitates a comprehensive understanding of macrophage interactions to optimize implant im...
Artificial intelligence (AI) systems substantially improve dermatologists' diagnostic accuracy for melanoma, with explainable AI (XAI) systems further...
Vision-Language Models (VLMs) have demonstrated impressive capabilities across a range of tasks, yet concerns about their potential biases exist. Th...
As vision-language models (VLMs) become increasingly integrated into daily life, the need for accurate visual culture understanding is becoming crit...
Large Vision-Language Models (VLMs) have shown strong capabilities in multimodal understanding and reasoning, yet they are primarily constrained by ...
Due to the unidirectional masking mechanism, Decoder-Only models propagate information from left to right. LVLMs (Large Vision-Language Models) foll...