Artificial Intelligence Medical Compendium

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

Showing 59,941 to 59,950 of 228,014 articles

Insight: Interpretable Semantic Hierarchies in Vision-Language Encoders

arXiv
Language-aligned vision foundation models perform strongly across diverse downstream tasks. Yet, their learned representations remain opaque, making interpreting their decision-making hard. Recent works decompose these representations into human-inte... read more 

Discriminant Learning-based Colorspace for Blade Segmentation

arXiv
Suboptimal color representation often hinders accurate image segmentation, yet many modern algorithms neglect this critical preprocessing step. This work presents a novel multidimensional nonlinear discriminant analysis algorithm, Colorspace Discrimi... read more 

FastGHA: Generalized Few-Shot 3D Gaussian Head Avatars with Real-Time Animation

arXiv
Despite recent progress in 3D Gaussian-based head avatar modeling, efficiently generating high fidelity avatars remains a challenge. Current methods typically rely on extensive multi-view capture setups or monocular videos with per-identity optimizat... read more 

DisasterVQA: A Visual Question Answering Benchmark Dataset for Disaster Scenes

arXiv
Social media imagery provides a low-latency source of situational information during natural and human-induced disasters, enabling rapid damage assessment and response. While Visual Question Answering (VQA) has shown strong performance in general-pur... read more 

Probabilistic Deep Discriminant Analysis for Wind Blade Segmentation

arXiv
Linear discriminant analysis improves class separability but struggles with non-linearly separable data. To overcome this, we introduce Deep Discriminant Analysis (DDA), which directly optimizes the Fisher criterion utilizing deep networks. To ensure... read more 

OCCAM: Class-Agnostic, Training-Free, Prior-Free and Multi-Class Object Counting

arXiv
Class-Agnostic object Counting (CAC) involves counting instances of objects from arbitrary classes within an image. Due to its practical importance, CAC has received increasing attention in recent years. Most existing methods assume a single object c... read more 

OmniOVCD: Streamlining Open-Vocabulary Change Detection with SAM 3

arXiv
Change Detection (CD) is a fundamental task in remote sensing. It monitors the evolution of land cover over time. Based on this, Open-Vocabulary Change Detection (OVCD) introduces a new requirement. It aims to reduce the reliance on predefined catego... read more 

TractRLFusion: A GPT-Based Multi-Critic Policy Fusion Framework for Fiber Tractography

arXiv
Tractography plays a pivotal role in the non-invasive reconstruction of white matter fiber pathways, providing vital information on brain connectivity and supporting precise neurosurgical planning. Although traditional methods relied mainly on classi... read more 

Towards Visually Explaining Statistical Tests with Applications in Biomedical Imaging

arXiv
Deep neural two-sample tests have recently shown strong power for detecting distributional differences between groups, yet their black-box nature limits interpretability and practical adoption in biomedical analysis. Moreover, most existing post-hoc ... read more 

On the Role of Rotation Equivariance in Monocular 3D Human Pose Estimation

arXiv
Estimating 3D from 2D is one of the central tasks in computer vision. In this work, we consider the monocular setting, i.e. single-view input, for 3D human pose estimation (HPE). Here, the task is to predict a 3D point set of human skeletal joints fr... read more