Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 10,031 to 10,040 of 208,614 articles

ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement

arXiv May 25, 2026
Existing deep learning-based low-light enhancement methods are typically trained on limited datasets with single enhancement targets, which restricts their generalization ability and controllability in real-world applications. To overcome these limit... read more 
Computer Vision and Pattern Recognition

From Contrast to Consistency: Rethinking Event-based Continuous-Time Optical Flow Estimation

arXiv May 25, 2026
Estimating continuous optical flow is a fundamental yet challenging problem in dynamic visual perception. Event-based cameras, with microsecond latency and high dynamic range, capture brightness changes asynchronously, offering a unique opportunity t... read more 
Computer Vision and Pattern Recognition

From Contrast to Consistency: Rethinking Event-based Continuous-Time Optical Flow Estimation

arXiv May 25, 2026
Estimating continuous optical flow is a fundamental yet challenging problem in dynamic visual perception. Event-based cameras, with microsecond latency and high dynamic range, capture brightness changes asynchronously, offering a unique opportunity t... read more 
Computer Vision and Pattern Recognition

Mosaic: Compositional Multi-Concept Erasure via Vector Field Blending

arXiv May 25, 2026
Concept erasure has emerged as a key research direction for ensuring safe and ethical image synthesis in Text-to-Image (T2I) models. While existing studies have explored concept erasure across multiple concepts, they typically assume only a single ta... read more 
Computer Vision and Pattern Recognition cs.AI

Artifact Correction for Echo-Planar Imaging at Low-Field and Ultra-Low-Field MRI

arXiv May 25, 2026
Purpose: Echo-planar imaging (EPI) in low-field (LF) and ultra-low-field MRI (ULF) suffers from severe Nyquist ghost artifacts due to odd-even k-space misalignment. This study develops a reference-free artifact correction pipeline that reduces relian... read more 
Computer Vision and Pattern Recognition

How Far Has AI Come in Liver Fibrosis Staging? A Large-Scale Real-World Dataset and Benchmark

arXiv May 25, 2026
Despite years of methodological progress, how far AI has come in liver fibrosis staging has never been systematically evaluated under the heterogeneous, multi-center conditions that define clinical practice. To address this gap, we introduce LiFS, a ... read more 
Computer Vision and Pattern Recognition

Event-based Batting Impact Estimation

arXiv May 25, 2026
Estimating the precise timing of batting impact is crucial for understanding the rapid sensorimotor control. However, this task is challenging for RGB cameras due to insufficient temporal resolution and motion blur. Similarly, Inertial Measurement Un... read more 
Computer Vision and Pattern Recognition

ARMA-C3: A Contrastive ARMA Convolutional Framework for Unsupervised and Semi-supervised Classification

arXiv May 25, 2026
In biomedical and neurodegenerative disorders, accurate and early disease identification remains challenging due to the scarcity of labeled data and the complexity of imaging patterns. To address these challenges, we introduce ARMA-C3, a unified unsu... read more 
Computer Vision and Pattern Recognition

DRM: Diffusion-based Reward Model With Step-wise Guidance

arXiv May 25, 2026
Current mainstream methods of aligning diffusion models with human preferences typically employ VLM-based reward models. However, these reward models, pre-trained for semantic alignment, struggle to capture the essential perceptual qualities-such as ... read more 
Computer Vision and Pattern Recognition

Stochastic Estimation of the Layer-wise Hessian Trace for Monitoring Neural-network Training

arXiv May 25, 2026
The loss and the norm of its gradient separate the healthy and the pathological regimes of neural-network training only weakly, whilst the curvature of the empirical risk differs qualitatively between them but is inaccessible explicitly at parameter ... read more 
Machine Learning
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