Latest AI and machine learning research in work force for healthcare professionals.
Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms assume fixed intrinsics throughout a video, an assumption that often fails for real-world in-the-wild videos. Consequently, estimating per-frame intrinsics from RGB images is critical for making 3D methods robust to videos with dynamic intrinsics. InFlux previously advanced this research direction by...
Diffusion models achieve impressive image-generation quality but remain expensive at inference time. Diffusion distillation reduces sampling steps, yet many distilled models, including SDXL-Lightning and distribution matching distillation methods, suffer from degraded Fréchet Inception Distance (FID). We analyze this phenomenon through a PAC-style generalization bound. Our analysis suggests that a...
Visual regression testing (VRT) is a standard quality assurance step in modern software release pipelines. On every change, it re-renders user interfa...
Due to the scarcity of expert-annotated data, Semi-Supervised Medical Image Segmentation (SSMIS) has emerged as a promising approach. Many anatomical ...
Conventional reinforcement learning strategies for visual generation typically employ sample-wise reward functions, yet this practice frequently resul...
Dysregulation of post-translational modifications (PTMs) is associated with severe pathologies, including cancers and Alzheimer's disease. Despite the...
Precision medicine relies on accurate and generalizable predictions for patients across the spectrum of human diversity. Because capturing biological ...
Multi-modal image matching is essential for visual localization and multi-sensor fusion, but it is hindered by the scarcity of large-scale training da...
Single image super-resolution aims to reconstruct high-resolution (HR) images from low-resolution (LR) inputs. Training SR models typically requires p...
Vision-language models can produce confident answers on visually ambiguous inputs, resulting in biased predictions. Common entropy-based methods, such...
Dynamic contrast-enhanced cardiac CT enables time-resolved analysis of contrast filling and washout in the left atrium (LA) and left atrial appendage ...
Background: Computer vision-enabled airway workflows can turn airway video into timestamped model-observation fields, but later blinded review and tra...
Bioactive peptides are now central to cosmetic and dermatological actives, yet predicting whether a given sequence will reach its site of action in sk...
From protein structure prediction to novel protein generation, challenging protein engineering tasks have been made possible by advancements in machin...
Despite contributing substantially to clinician burnout, nursing documentation lacks empirical evidence distinguishing clinically essential from admin...
State-of-the-art flow models generate stunning images from text or image prompts. However, they suffer from diversity collapse when generating multipl...
Introduction Stillbirth prevention requires reliable detection of potential causes for timely interventions. Currently, there is no effective screenin...
Alzheimer's Disease is a chronic neurodegenerative disorder projected to affect 115 million people by 2050, driven by mechanisms like the cholinergic ...
Subject-driven image generation faces an "Identity-Diversity Paradox", where strong identity preservation often leads to rigid and low-diversity outpu...
Mental health assessment commonly relies on isolated screening instruments or data-driven models that often lack interpretability and multi-dimensiona...