Artificial Intelligence Medical Compendium

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

Showing 41,781 to 41,790 of 223,853 articles

Personalized Cell Segmentation: Benchmark and Framework for Reference-Guided Cell Type Segmentation

arXiv Mar 15, 2026
Accurate cell segmentation is critical for biological and medical imaging studies. Although recent deep learning models have advanced this task, most methods are limited to generic cell segmentation, lacking the ability to differentiate specific cell... read more 
Computer Vision and Pattern Recognition

How Do Medical MLLMs Fail? A Study on Visual Grounding in Medical Images

arXiv Mar 15, 2026
Generalist multimodal large language models (MLLMs) have achieved impressive performance across a wide range of vision-language tasks. However, their performance on medical tasks, particularly in zero-shot settings where generalization is critical, r... read more 
Computer Vision and Pattern Recognition cs.AI

ECG-Reasoning-Benchmark: A Benchmark for Evaluating Clinical Reasoning Capabilities in ECG Interpretation

arXiv Mar 15, 2026
While Multimodal Large Language Models (MLLMs) show promising performance in automated electrocardiogram interpretation, it remains unclear whether they genuinely perform actual step-by-step reasoning or just rely on superficial visual cues. To inves... read more 
Machine Learning cs.AI cs.CL

UAVBench and UAVIT-1M: Benchmarking and Enhancing MLLMs for Low-Altitude UAV Vision-Language Understanding

arXiv Mar 15, 2026
Multimodal Large Language Models (MLLMs) have made significant strides in natural images and satellite remote sensing images. However, understanding low-altitude drone scenarios remains a challenge. Existing datasets primarily focus on a few specific... read more 
Computer Vision and Pattern Recognition

Representation Alignment for Just Image Transformers is not Easier than You Think

arXiv Mar 15, 2026
Representation Alignment (REPA) has emerged as a simple way to accelerate Diffusion Transformers training in latent space. At the same time, pixel-space diffusion transformers such as Just image Transformers (JiT) have attracted growing attention bec... read more 
Computer Vision and Pattern Recognition cs.LG

StAR: Segment Anything Reasoner

arXiv Mar 15, 2026
As AI systems are being integrated more rapidly into diverse and complex real-world environments, the ability to perform holistic reasoning over an implicit query and an image to localize a target is becoming increasingly important. However, recent r... read more 
Computer Vision and Pattern Recognition

OCRA: Object-Centric Learning with 3D and Tactile Priors for Human-to-Robot Action Transfer

arXiv Mar 15, 2026
We present OCRA, an Object-Centric framework for video-based human-to-Robot Action transfer that learns directly from human demonstration videos to enable robust manipulation. Object-centric learning emphasizes task-relevant objects and their interac... read more 
Robotics cs.CV

PGcGAN: Pathological Gait-Conditioned GAN for Human Gait Synthesis

arXiv Mar 15, 2026
Pathological gait analysis is constrained by limited and variable clinical datasets, which restrict the modeling of diverse gait impairments. To address this challenge, we propose a Pathological Gait-conditioned Generative Adversarial Network (PGcGAN... read more 
Computer Vision and Pattern Recognition cs.AI

G-ZAP: A Generalizable Zero-Shot Framework for Arbitrary-Scale Pansharpening

arXiv Mar 15, 2026
Pansharpening aims to fuse a high-resolution panchromatic (PAN) image and a low-resolution multispectral (LRMS) image to produce a high-resolution multispectral (HRMS) image. Recent deep models have achieved strong performance, yet they typically rel... read more 
Computer Vision and Pattern Recognition

Coefficient pairing with centralized regularization for structured sparsity.

Neural networks : the official journal of the International Neural Network Society Mar 15, 2026
Sparse linear regression is widely used, yet challenges remain under strong predictor correlation and when coefficients exhibit latent group structure not implied by covariate correlation. We propose coefficient-paired estimation with centralized reg... read more 
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