Ophthalmology

INSIGHT: Enhancing Autonomous Driving Safety through Vision-Language Models on Context-Aware Hazard Detection and Edge Case Evaluation

Autonomous driving systems face significant challenges in handling unpredictable edge-case scenarios, such as adversarial pedestrian movements, dangerous vehicle maneuvers, and sudden environmental changes. Current end-to-end driving models struggle with generalization to these rare events due to limitations in traditional detection and prediction approaches. To address this, we propose INSIGHT ...

INSIGHT: Combining Fixation Visualisations and Residual Neural Networks for Dyslexia Classification From Eye-Tracking Data.

Current diagnostic methods for dyslexia primarily rely on traditional paper-and-pencil tasks. Advanced technological approaches, including eye-tracking and artificial intelligence (AI), offer enhanced diagnostic capabilities. In this paper, we bridge the gap between scientific and diagnostic concepts by proposing a novel dyslexia detection method, called INSIGHT, which combines a visualisation pha...

Scale to predict risk for refractory septic shock based on a hybrid approach using machine learning and regression modeling.

OBJECTIVE: To develop a scale to predict refractory septic shock (SS) based on clinical variables recorded during initial evaluations of patients.

A Novel Technique for Eye Rejuvenation: A Case Series of the Combined Use of CO Laser Blepharoplasty and Erbium: YAG Resurfacing and A Novel Artificial Intelligence Model to Quantify Laser Results.

BACKGROUND: Consumers are searching for a solution to rejuvenate the eye area. Surgical blepharoplasties are a common solution, but they lack improvem...

Evaluating Deep Human-in-the-Loop Optimization for Retinal Implants Using Sighted Participants

Human-in-the-loop optimization (HILO) is a promising approach for personalizing visual prostheses by iteratively refining stimulus parameters based ...

PixelWorld: Towards Perceiving Everything as Pixels

Recent agentic language models increasingly need to interact directly with real-world environments containing intertwined visual and textual informa...

RLS3: RL-Based Synthetic Sample Selection to Enhance Spatial Reasoning in Vision-Language Models for Indoor Autonomous Perception

Vision-language model (VLM) fine-tuning for application-specific visual grounding based on natural language instructions has become one of the most ...

A New Statistical Approach to the Performance Analysis of Vision-based Localization

Many modern wireless devices with accurate positioning needs also have access to vision sensors, such as a camera, radar, and Light Detection and Ra...

UDC-VIT: A Real-World Video Dataset for Under-Display Cameras

Under Display Camera (UDC) is an advanced imaging system that places a digital camera lens underneath a display panel, effectively concealing the ca...

Rethinking Bottlenecks in Safety Fine-Tuning of Vision Language Models

Large Vision-Language Models (VLMs) have achieved remarkable performance across a wide range of tasks. However, their deployment in safety-critical ...

Integrating Spatial and Frequency Information for Under-Display Camera Image Restoration

Under-Display Camera (UDC) houses a digital camera lens under a display panel. However, UDC introduces complex degradations such as noise, blur, dec...

Arbitrary Data as Images: Fusion of Patient Data Across Modalities and Irregular Intervals with Vision Transformers

A patient undergoes multiple examinations in each hospital stay, where each provides different facets of the health status. These assessments includ...

[Intelligent Monitoring System Based on Computer Vision and Artificial Intelligence].

To ensure the quality of care for inpatients in ophthalmic hospitals, address the complex and variable conditions of postoperative patients, and condu...

Exploring Vision Language Models for Multimodal and Multilingual Stance Detection

Social media's global reach amplifies the spread of information, highlighting the need for robust Natural Language Processing tasks like stance dete...

Dual Invariance Self-training for Reliable Semi-supervised Surgical Phase Recognition

Accurate surgical phase recognition is crucial for advancing computer-assisted interventions, yet the scarcity of labeled data hinders training reli...

Influence of field of view in visual prostheses design: Analysis with a VR system

Visual prostheses are designed to restore partial functional vision in patients with total vision loss. Retinal visual prostheses provide limited ca...

ViT-2SPN: Vision Transformer-based Dual-Stream Self-Supervised Pretraining Networks for Retinal OCT Classification

Optical Coherence Tomography (OCT) is a non-invasive imaging modality essential for diagnosing various eye diseases. Despite its clinical significan...

3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow

3D vision and spatial reasoning have long been recognized as preferable for accurately perceiving our three-dimensional world, especially when compa...

SliceOcc: Indoor 3D Semantic Occupancy Prediction with Vertical Slice Representation

3D semantic occupancy prediction is a crucial task in visual perception, as it requires the simultaneous comprehension of both scene geometry and se...

Object Detection for Medical Image Analysis: Insights from the RT-DETR Model

Deep learning has emerged as a transformative approach for solving complex pattern recognition and object detection challenges. This paper focuses o...