Artificial Intelligence Medical Compendium

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

Showing 55,481 to 55,490 of 226,647 articles

Your AI-Generated Image Detector Can Secretly Achieve SOTA Accuracy, If Calibrated

arXiv
Despite being trained on balanced datasets, existing AI-generated image detectors often exhibit systematic bias at test time, frequently misclassifying fake images as real. We hypothesize that this behavior stems from distributional shift in fake sam... read more 

Grounding Generated Videos in Feasible Plans via World Models

arXiv
Large-scale video generative models have shown emerging capabilities as zero-shot visual planners, yet video-generated plans often violate temporal consistency and physical constraints, leading to failures when mapped to executable actions. To addres... read more 

Beyond Open Vocabulary: Multimodal Prompting for Object Detection in Remote Sensing Images

arXiv
Open-vocabulary object detection in remote sensing commonly relies on text-only prompting to specify target categories, implicitly assuming that inference-time category queries can be reliably grounded through pretraining-induced text-visual alignmen... read more 

Deep Multivariate Models with Parametric Conditionals

arXiv
We consider deep multivariate models for heterogeneous collections of random variables. In the context of computer vision, such collections may e.g. consist of images, segmentations, image attributes, and latent variables. When developing such models... read more 

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

arXiv
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 

LIEREx: Language-Image Embeddings for Robotic Exploration

arXiv
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 

Bayesian Integration of Nonlinear Incomplete Clinical Data

arXiv
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 

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

arXiv
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 

Learning Sparse Visual Representations via Spatial-Semantic Factorization

arXiv
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 

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

arXiv
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