Artificial Intelligence Medical Compendium

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

Showing 47,701 to 47,710 of 224,199 articles

One2Scene: Geometric Consistent Explorable 3D Scene Generation from a Single Image

arXiv Feb 23, 2026
Generating explorable 3D scenes from a single image is a highly challenging problem in 3D vision. Existing methods struggle to support free exploration, often producing severe geometric distortions and noisy artifacts when the viewpoint moves far fro... read more 
Computer Vision and Pattern Recognition

TraceVision: Trajectory-Aware Vision-Language Model for Human-Like Spatial Understanding

arXiv Feb 23, 2026
Recent Large Vision-Language Models (LVLMs) demonstrate remarkable capabilities in image understanding and natural language generation. However, current approaches focus predominantly on global image understanding, struggling to simulate human visual... read more 
Computer Vision and Pattern Recognition

TraceVision: Trajectory-Aware Vision-Language Model for Human-Like Spatial Understanding

arXiv Feb 23, 2026
Recent Large Vision-Language Models (LVLMs) demonstrate remarkable capabilities in image understanding and natural language generation. However, current approaches focus predominantly on global image understanding, struggling to simulate human visual... read more 
Computer Vision and Pattern Recognition

Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings

arXiv Feb 23, 2026
Meta-learning methods perform well on new within-distribution tasks but often fail when adapting to out-of-distribution target tasks, where transfer from source tasks can induce negative transfer. We propose a causally-aware Bayesian meta-learning me... read more 
Machine Learning

Drift Localization using Conformal Predictions

arXiv Feb 23, 2026
Concept drift -- the change of the distribution over time -- poses significant challenges for learning systems and is of central interest for monitoring. Understanding drift is thus paramount, and drift localization -- determining which samples are a... read more 
Machine Learning stat.ML

Efficient endometrial carcinoma screening via cross-modal synthesis and gradient distillation

arXiv Feb 23, 2026
Early detection of myometrial invasion is critical for the staging and life-saving management of endometrial carcinoma (EC), a prevalent global malignancy. Transvaginal ultrasound serves as the primary, accessible screening modality in resource-const... read more 
Computer Vision and Pattern Recognition cs.AI

TextShield-R1: Reinforced Reasoning for Tampered Text Detection

arXiv Feb 23, 2026
The growing prevalence of tampered images poses serious security threats, highlighting the urgent need for reliable detection methods. Multimodal large language models (MLLMs) demonstrate strong potential in analyzing tampered images and generating i... read more 
Computer Vision and Pattern Recognition

M3S-Net: Multimodal Feature Fusion Network Based on Multi-scale Data for Ultra-short-term PV Power Forecasting

arXiv Feb 23, 2026
The inherent intermittency and high-frequency variability of solar irradiance, particularly during rapid cloud advection, present significant stability challenges to high-penetration photovoltaic grids. Although multimodal forecasting has emerged as ... read more 
Computer Vision and Pattern Recognition

DerMAE: Improving skin lesion classification through conditioned latent diffusion and MAE distillation

arXiv Feb 23, 2026
Skin lesion classification datasets often suffer from severe class imbalance, with malignant cases significantly underrepresented, leading to biased decision boundaries during deep learning training. We address this challenge using class-conditioned ... read more 
Computer Vision and Pattern Recognition

Contrastive meta-domain adaptation for robust skin lesion classification across clinical and acquisition conditions

arXiv Feb 23, 2026
Deep learning models for dermatological image analysis remain sensitive to acquisition variability and domain-specific visual characteristics, leading to performance degradation when deployed in clinical settings. We investigate how visual artifacts ... read more 
Computer Vision and Pattern Recognition
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