Artificial Intelligence Medical Compendium

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

Showing 62,211 to 62,220 of 230,319 articles

Vision-Based Natural Language Scene Understanding for Autonomous Driving: An Extended Dataset and a New Model for Traffic Scene Description Generation

arXiv Jan 20, 2026
Traffic scene understanding is essential for enabling autonomous vehicles to accurately perceive and interpret their environment, thereby ensuring safe navigation. This paper presents a novel framework that transforms a single frontal-view camera ima... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL cs.LG

VisTIRA: Closing the Image-Text Modality Gap in Visual Math Reasoning via Structured Tool Integration

arXiv Jan 20, 2026
Vision-language models (VLMs) lag behind text-only language models on mathematical reasoning when the same problems are presented as images rather than text. We empirically characterize this as a modality gap: the same question in text form yields ma... read more 
Artificial Intelligence cs.CL cs.LG

Real-Time Wildfire Localization on the NASA Autonomous Modular Sensor using Deep Learning

arXiv Jan 20, 2026
High-altitude, multi-spectral, aerial imagery is scarce and expensive to acquire, yet it is necessary for algorithmic advances and application of machine learning models to high-impact problems such as wildfire detection. We introduce a human-annotat... read more 
Computer Vision and Pattern Recognition cs.AI

XD-MAP: Cross-Modal Domain Adaptation using Semantic Parametric Mapping

arXiv Jan 20, 2026
Until open-world foundation models match the performance of specialized approaches, the effectiveness of deep learning models remains heavily dependent on dataset availability. Training data must align not only with the target object categories but a... read more 
Computer Vision and Pattern Recognition cs.AI eess.IV

PAS-Mamba: Phase-Amplitude-Spatial State Space Model for MRI Reconstruction

arXiv Jan 20, 2026
Joint feature modeling in both the spatial and frequency domains has become a mainstream approach in MRI reconstruction. However, existing methods generally treat the frequency domain as a whole, neglecting the differences in the information carried ... read more 
Computer Vision and Pattern Recognition

engGNN: A Dual-Graph Neural Network for Omics-Based Disease Classification and Feature Selection

arXiv Jan 20, 2026
Omics data, such as transcriptomics, proteomics, and metabolomics, provide critical insights into disease mechanisms and clinical outcomes. However, their high dimensionality, small sample sizes, and intricate biological networks pose major challenge... read more 
Machine Learning q-bio.GN stat.ML

Optical Linear Systems Framework for Event Sensing and Computational Neuromorphic Imaging

arXiv Jan 20, 2026
Event vision sensors (neuromorphic cameras) output sparse, asynchronous ON/OFF events triggered by log-intensity threshold crossings, enabling microsecond-scale sensing with high dynamic range and low data bandwidth. As a nonlinear system, this event... read more 
Computer Vision and Pattern Recognition

GO-MLVTON: Garment Occlusion-Aware Multi-Layer Virtual Try-On with Diffusion Models

arXiv Jan 20, 2026
Existing Image-based virtual try-on (VTON) methods primarily focus on single-layer or multi-garment VTON, neglecting multi-layer VTON (ML-VTON), which involves dressing multiple layers of garments onto the human body with realistic deformation and la... read more 
Computer Vision and Pattern Recognition

MN-TSG:Continuous Time Series Generation with Irregular Observations

arXiv Jan 20, 2026
Time series generation (TSG) plays a critical role in a wide range of domains, such as healthcare. However, most existing methods assume regularly sampled observations and fixed output resolutions, which are often misaligned with real-world scenarios... read more 
Machine Learning cs.AI

DiffFace-Edit: A Diffusion-Based Facial Dataset for Forgery-Semantic Driven Deepfake Detection Analysis

arXiv Jan 20, 2026
Generative models now produce imperceptible, fine-grained manipulated faces, posing significant privacy risks. However, existing AI-generated face datasets generally lack focus on samples with fine-grained regional manipulations. Furthermore, no rese... read more 
Computer Vision and Pattern Recognition
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