Artificial Intelligence Medical Compendium

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

Showing 16,191 to 16,200 of 213,568 articles

Aerodynamic force reconstruction using physics-informed Gaussian processes

arXiv
Accurate modeling of aerodynamic loads is essential for understanding and predicting the responses of complex structural systems. However, these models often rely on simplifications of the true physical forces, introducing assumptions that can limit ... read more 

MotionDPS: Motion-Compensated 3D Brain MRI Reconstruction

arXiv
Magnetic resonance imaging (MRI) is highly susceptible to patient motion due to its relatively long acquisition times and the fact that data are acquired sequentially in k-space. Even small patient movements introduce phase inconsistencies across mea... read more 

AesFormer: Transform Everyday Photos into Beautiful Memories

arXiv
In everyday photography, aesthetically appealing moments are often captured with structural flaws (e.g., composition, camera viewpoint, or pose) that existing retouching and portrait enhancement methods cannot fix. We formulate Aesthetic Photo Recons... read more 

Accelerating Vision Foundation Models with Drop-in Depthwise Convolution

arXiv
Pretrained vision foundation models deliver strong performance across tasks with limited fine-tuning. However, their Vision Transformer (ViT) backbones impose high inference costs, limiting deployment on resource-constrained devices. In this work, we... read more 

EventGait: Towards Robust Gait Recognition with Event Streams

arXiv
Gait recognition enables non-intrusive, privacy-preserving identification but suffers in uncontrolled environments due to illumination and motion sensitivity of conventional cameras. In this work, we explore gait recognition using event cameras, whic... read more 

Flow-based Gaussian Splatting for Continuous-Scale Remote Sensing Image Super-Resolution

arXiv
High-resolution remote sensing images (RSIs) are crucial for Earth observation applications, yet acquiring them is often limited by sensor constraints and costs. In recent years, generative super-resolution (SR) methods, particularly diffusion models... read more 

Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines

arXiv
Symbolic methods are generally not considered competitive with strong modern learners on realistic supervised tasks. We evaluate Algebraic Machine Learning (AML), a framework that learns through subdirect decomposition of algebraic structure rather t... read more 

Event-Illumination Collaborative Low-light Image Enhancement with a High-resolution Real-world Dataset

arXiv
Event-based low-light image enhancement (LIE) methods mainly focus on incorporating high dynamic range (HDR) information from events while overlooking the essential global illumination in images and the inherent noise sensitivity of event signals in ... read more 

No Pose, No Problem in 4D: Feed-Forward Dynamic Gaussians from Unposed Multi-View Videos

arXiv
Recent feed-forward 3D gaussian splatting methods have made dramatic progress on individual aspects of 3D scene reconstruction, but no existing method jointly addresses dynamic content, multi-view input, and unknown camera poses in a single feed-forw... read more 

Ultra-High-Definition Image Quality Assessment via Graph Representation Learning

arXiv
Blind image quality assessment (BIQA) for ultrahighdefinition (UHD) images remains challenging because native-resolution inference is computationally expensive, whereas aggressive resizing or isolated cropping may suppress scale-sensitive distortions... read more