Refractive Surgery

Three-in-One: Robust Enhanced Universal Transferable Anti-Facial Retrieval in Online Social Networks

Deep hash-based retrieval techniques are widely used in facial retrieval systems to improve the efficiency of facial matching. However, it also carries the danger of exposing private information. Deep hash models are easily influenced by adversarial examples, which can be leveraged to protect private images from malicious retrieval. The existing adversarial example methods against deep hash mode...

Graph convolutional networks enable fast hemorrhagic stroke monitoring with electrical impedance tomography

Objective: To develop a fast image reconstruction method for stroke monitoring with electrical impedance tomography with image quality comparable to computationally expensive nonlinear model-based methods. Methods: A post-processing approach with graph convolutional networks is employed. Utilizing the flexibility of the graph setting, a graph U-net is trained on linear difference reconstructions...

Hyperbolic embedding of brain networks can predict the surgery outcome in temporal lobe epilepsy

Epilepsy surgery, particularly for temporal lobe epilepsy (TLE), remains a vital treatment option for patients with drug-resistant seizures. However...

A Pipeline and NIR-Enhanced Dataset for Parking Lot Segmentation

Discussions of minimum parking requirement policies often include maps of parking lots, which are time consuming to construct manually. Open source ...

Take Fake as Real: Realistic-like Robust Black-box Adversarial Attack to Evade AIGC Detection

The security of AI-generated content (AIGC) detection is crucial for ensuring multimedia content credibility. To enhance detector security, research...

Automated Dynamic Image Analysis for Particle Size and Shape Classification in Three Dimensions

We introduce OCULAR, an innovative hardware and software solution for three-dimensional dynamic image analysis of fine particles. Current state-of-t...

Multiclass Post-Earthquake Building Assessment Integrating Optical and SAR Satellite Imagery, Ground Motion, and Soil Data with Transformers

Timely and accurate assessments of building damage are crucial for effective response and recovery in the aftermath of earthquakes. Conventional pre...

Benchmarking Attention Mechanisms and Consistency Regularization Semi-Supervised Learning for Post-Flood Building Damage Assessment in Satellite Images

Post-flood building damage assessment is critical for rapid response and post-disaster reconstruction planning. Current research fails to consider t...

The Trusted Caregiver: The Influence of Eye and Mouth Design Incorporating the Baby Schema Effect in Virtual Humanoid Agents on Older Adults Users' Perception of Trustworthiness

The increasing proportion of the older adult population has made the smart home care industry one of the critical markets for virtual human-like age...

ML-Based Framework to Predict the Severity of the Symptomatology in Patients with Post-Acute COVID-19 Syndrome.

The paper describes a cohort of patients with post-acute COVID-19 syndrome, evaluated for the first time between week 3 and week 12 from the onset of ...

Deep operator network models for predicting post-burn contraction

Burn injuries present a significant global health challenge. Among the most severe long-term consequences are contractures, which can lead to functi...

Explainability of Point Cloud Neural Networks Using SMILE: Statistical Model-Agnostic Interpretability with Local Explanations

In today's world, the significance of explainable AI (XAI) is growing in robotics and point cloud applications, as the lack of transparency in decis...

Seizure freedom after surgical resection of diffusion-weighted MRI abnormalities

Importance: Many individuals with drug-resistant epilepsy continue to have seizures after resective surgery. Accurate identification of focal brain ...

Examining the Role of Relationship Alignment in Large Language Models

The rapid development and deployment of Generative AI in social settings raise important questions about how to optimally personalize them for users...

Retrospective Comparative Analysis of Prostate Cancer In-Basket Messages: Responses from Closed-Domain LLM vs. Clinical Teams

In-basket message interactions play a crucial role in physician-patient communication, occurring during all phases (pre-, during, and post) of a pat...

A Lesion-aware Edge-based Graph Neural Network for Predicting Language Ability in Patients with Post-stroke Aphasia

We propose a lesion-aware graph neural network (LEGNet) to predict language ability from resting-state fMRI (rs-fMRI) connectivity in patients with ...

Deep Neural Networks for Predicting Recurrence and Survival in Patients with Esophageal Cancer After Surgery

Esophageal cancer is a major cause of cancer-related mortality internationally, with high recurrence rates and poor survival even among patients tre...

Machine Learning Models for Predicting Cycloplegic Refractive Error and Myopia Status Based on Non-Cycloplegic Data in Chinese Students.

PURPOSE: To develop and validate machine learning (ML) models for predicting cycloplegic refractive error and myopia status using noncycloplegic refra...

Deep Learning-Based Longitudinal Prediction of Childhood Myopia Progression Using Fundus Image Sequences and Baseline Refraction Data

Childhood myopia constitutes a significant global health concern. It exhibits an escalating prevalence and has the potential to evolve into severe, ...

Standard compliant video coding using low complexity, switchable neural wrappers

The proliferation of high resolution videos posts great storage and bandwidth pressure on cloud video services, driving the development of next-gene...