Artificial Intelligence Medical Compendium

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

Showing 54,861 to 54,870 of 226,183 articles

WS-IMUBench: Can Weakly Supervised Methods from Audio, Image, and Video Be Adapted for IMU-based Temporal Action Localization?

arXiv Feb 2, 2026
IMU-based Human Activity Recognition (HAR) has enabled a wide range of ubiquitous computing applications, yet its dominant clip classification paradigm cannot capture the rich temporal structure of real-world behaviors. This motivates a shift toward ... read more 
Computer Vision and Pattern Recognition

How Well Do Models Follow Visual Instructions? VIBE: A Systematic Benchmark for Visual Instruction-Driven Image Editing

arXiv Feb 2, 2026
Recent generative models have achieved remarkable progress in image editing. However, existing systems and benchmarks remain largely text-guided. In contrast, human communication is inherently multimodal, where visual instructions such as sketches ef... read more 
Computer Vision and Pattern Recognition

Fact or Fake? Assessing the Role of Deepfake Detectors in Multimodal Misinformation Detection

arXiv Feb 2, 2026
In multimodal misinformation, deception usually arises not just from pixel-level manipulations in an image, but from the semantic and contextual claim jointly expressed by the image-text pair. Yet most deepfake detectors, engineered to detect pixel-l... read more 
Computer Vision and Pattern Recognition

Trust but Verify: Adaptive Conditioning for Reference-Based Diffusion Super-Resolution via Implicit Reference Correlation Modeling

arXiv Feb 2, 2026
Recent works have explored reference-based super-resolution (RefSR) to mitigate hallucinations in diffusion-based image restoration. A key challenge is that real-world degradations make correspondences between low-quality (LQ) inputs and reference (R... read more 
Computer Vision and Pattern Recognition

ProxyImg: Towards Highly-Controllable Image Representation via Hierarchical Disentangled Proxy Embedding

arXiv Feb 2, 2026
Prevailing image representation methods, including explicit representations such as raster images and Gaussian primitives, as well as implicit representations such as latent images, either suffer from representation redundancy that leads to heavy man... read more 
Computer Vision and Pattern Recognition

Learning Sparse Visual Representations via Spatial-Semantic Factorization

arXiv Feb 2, 2026
Self-supervised learning (SSL) faces a fundamental conflict between semantic understanding and image reconstruction. High-level semantic SSL (e.g., DINO) relies on global tokens that are forced to be location-invariant for augmentation alignment, a p... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

DSXFormer: Dual-Pooling Spectral Squeeze-Expansion and Dynamic Context Attention Transformer for Hyperspectral Image Classification

arXiv Feb 2, 2026
Hyperspectral image classification (HSIC) is a challenging task due to high spectral dimensionality, complex spectral-spatial correlations, and limited labeled training samples. Although transformer-based models have shown strong potential for HSIC, ... read more 
Computer Vision and Pattern Recognition cs.AI

Bayesian Integration of Nonlinear Incomplete Clinical Data

arXiv Feb 2, 2026
Multimodal clinical data are characterized by high dimensionality, heterogeneous representations, and structured missingness, posing significant challenges for predictive modeling, data integration, and interpretability. We propose BIONIC (Bayesian I... read more 
Machine Learning cs.CY

LIEREx: Language-Image Embeddings for Robotic Exploration

arXiv Feb 2, 2026
Semantic maps allow a robot to reason about its surroundings to fulfill tasks such as navigating known environments, finding specific objects, and exploring unmapped areas. Traditional mapping approaches provide accurate geometric representations but... read more 
Robotics cs.CV

Enabling Progressive Whole-slide Image Analysis with Multi-scale Pyramidal Network

arXiv Feb 2, 2026
Multiple-instance Learning (MIL) is commonly used to undertake computational pathology (CPath) tasks, and the use of multi-scale patches allows diverse features across scales to be learned. Previous studies using multi-scale features in clinical appl... read more 
Computer Vision and Pattern Recognition
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