Artificial Intelligence Medical Compendium

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

Showing 10,671 to 10,680 of 209,601 articles

HydraPrompt: An Adaptive and Asymmetric Framework of Vision-Language Models for Synthetic Image Detection

arXiv May 26, 2026
The rapid evolution of generative models has precipitated a proliferation of fabricated content, posing significant challenges to existing Synthetic Image Detection (SID) methods. Capitalizing on advancements in vision-language models (e.g., CLIP), r... read more 
Computer Vision and Pattern Recognition

FM-fMRI: Event Conditioned Flow Matching for Rest-to-Task fMRI Time-Series Synthesis

arXiv May 26, 2026
Task-based fMRI provides a direct readout of task-evoked neural dynamics, but it is expensive and difficult to acquire at scale, motivating rest-to-task synthesis from widely available resting-state fMRI (rsfMRI). We propose FM-fMRI, an event-conditi... read more 
Machine Learning eess.IV

Underwater360: Reconstructing Underwater Scenes from Panoramic Images with Omnidirectional Gaussian Splatting

arXiv May 26, 2026
Underwater scene reconstruction is essential for immersive exploration of aquatic environments, yet remains challenging due to complex participating-media effects such as absorption and scattering, as well as the limited field of view (FoV) of conven... read more 
Computer Vision and Pattern Recognition

Cross-scale Aligned Supervision for Training GANs

arXiv May 26, 2026
Modern GANs often introduce adversarial supervision on intermediate generator outputs and interpret the resulting multi-stage synthesis as coarse-to-fine hierarchical generation. In this work, we challenge this interpretation. We argue that standard ... read more 
Computer Vision and Pattern Recognition cs.AI

AnchorDiff: Training-Free Concept Grounding for MM-DiTs via Anchor-Based Graph Propagation

arXiv May 26, 2026
Multi-Modal Diffusion Transformers (MM-DiTs) encode rich representations for training-free concept grounding, but existing attention-based methods often produce overlapping activations on visually confusable concepts, a failure mode we call concept l... read more 
Computer Vision and Pattern Recognition cs.AI

Diffuse to Detect: Generative Diffusion Models for Unsupervised IC Anomaly Detection

arXiv May 26, 2026
Latent defect screening is challenged by extremely low failure rates, high-dimensional test data, and absence of labeled anomalies. We propose the first unsupervised anomaly detection framework incorporating a Diffusion Transformer. Raw test measurem... read more 
Machine Learning cs.AI

Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules

arXiv May 26, 2026
Generative posterior sampling using diffusion models has emerged as a dominant paradigm for solving inverse problems in imaging, which usually consists of three main components: data consistency (DC) guidance, classifier-free guidance (CFG) and stoch... read more 
Computer Vision and Pattern Recognition

Comparative Study of Vision-Based Metric Measurement for Large-Scale Planar Scenes

arXiv May 26, 2026
Vision-based metric distance and area measurement remains challenging in large-scale outdoor environments due to long-range sensing, camera zoom, and unstable imaging conditions. This work studies planar metric measurement in a real-world reservoir m... read more 
Computer Vision and Pattern Recognition cs.AI

Variational Inference for Evidential Deep Learning

arXiv May 26, 2026
While Deep Neural Networks (DNNs) achieve remarkable performance, their tendency to produce overconfident predictions. Evidential Deep Learning (EDL) mitigates this by formulating predictions as a Dirichlet distribution over class probabilities to ex... read more 
Machine Learning

Clinically-Grounded Counterfactual Reasoning for Medical Video Diagnosis

arXiv May 26, 2026
Medical video diagnosis involves inferring clinical decisions from dynamic tissue responses throughout examination processes. Existing methods rely on an end-to-end learning paradigm that i) focuses on appearance rather than pathology, ii) lacks clin... read more 
Computer Vision and Pattern Recognition
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