Artificial Intelligence Medical Compendium

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

Showing 49,311 to 49,320 of 224,513 articles

Explainability for Fault Detection System in Chemical Processes

arXiv Feb 18, 2026
In this work, we apply and compare two state-of-the-art eXplainability Artificial Intelligence (XAI) methods, the Integrated Gradients (IG) and the SHapley Additive exPlanations (SHAP), that explain the fault diagnosis decisions of a highly accurate ... read more 
Machine Learning

SCAR: Satellite Imagery-Based Calibration for Aerial Recordings

arXiv Feb 18, 2026
We introduce SCAR, a method for long-term auto-calibration refinement of aerial visual-inertial systems that exploits georeferenced satellite imagery as a persistent global reference. SCAR estimates both intrinsic and extrinsic parameters by aligning... read more 
Computer Vision and Pattern Recognition cs.RO

Optical Inversion and Spectral Unmixing of Spectroscopic Photoacoustic Images with Physics-Informed Neural Networks

arXiv Feb 18, 2026
Accurate estimation of the relative concentrations of chromophores in a spectroscopic photoacoustic (sPA) image can reveal immense structural, functional, and molecular information about physiological processes. However, due to nonlinearities and ill... read more 
Machine Learning q-bio.QM

Automated Histopathology Report Generation via Pyramidal Feature Extraction and the UNI Foundation Model

arXiv Feb 18, 2026
Generating diagnostic text from histopathology whole slide images (WSIs) is challenging due to the gigapixel scale of the input and the requirement for precise, domain specific language. We propose a hierarchical vision language framework that combin... read more 
Image and Video Processing cs.AI cs.CV

DressWild: Feed-Forward Pose-Agnostic Garment Sewing Pattern Generation from In-the-Wild Images

arXiv Feb 18, 2026
Recent advances in garment pattern generation have shown promising progress. However, existing feed-forward methods struggle with diverse poses and viewpoints, while optimization-based approaches are computationally expensive and difficult to scale. ... read more 
Computer Vision and Pattern Recognition

Arc2Morph: Identity-Preserving Facial Morphing with Arc2Face

arXiv Feb 18, 2026
Face morphing attacks are widely recognized as one of the most challenging threats to face recognition systems used in electronic identity documents. These attacks exploit a critical vulnerability in passport enrollment procedures adopted by many cou... read more 
Computer Vision and Pattern Recognition cs.CR

Steering diffusion models with quadratic rewards: a fine-grained analysis

arXiv Feb 18, 2026
Inference-time algorithms are an emerging paradigm in which pre-trained models are used as subroutines to solve downstream tasks. Such algorithms have been proposed for tasks ranging from inverse problems and guided image generation to reasoning. How... read more 
Machine Learning cs.DS

A Contrastive Learning Framework Empowered by Attention-based Feature Adaptation for Street-View Image Classification

arXiv Feb 18, 2026
Street-view image attribute classification is a vital downstream task of image classification, enabling applications such as autonomous driving, urban analytics, and high-definition map construction. It remains computationally demanding whether train... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Error Propagation and Model Collapse in Diffusion Models: A Theoretical Study

arXiv Feb 18, 2026
Machine learning models are increasingly trained or fine-tuned on synthetic data. Recursively training on such data has been observed to significantly degrade performance in a wide range of tasks, often characterized by a progressive drift away from ... read more 
Machine Learning cs.LG

Explainable AI: Context-Aware Layer-Wise Integrated Gradients for Explaining Transformer Models

arXiv Feb 18, 2026
Transformer models achieve state-of-the-art performance across domains and tasks, yet their deeply layered representations make their predictions difficult to interpret. Existing explainability methods rely on final-layer attributions, capture either... read more 
Computation and Language cs.AI cs.CV cs.LG
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