Latest AI and machine learning research in covid-19 for healthcare professionals.
Volumetric Reasoning Segmentation (VRS) aims to segment a target region in a 3D medical scan from a free-form clinical query, where the referent is often implicit and requires both medical knowledge and volume-grounded reasoning. Existing methods typically rely on specialized segmentation tokens to connect language with mask decoding, but this coupling collapses the decision process into opaque la...
Distilling demonstration effects into hidden-space interventions offers a lightweight alternative to full finetuning. However, existing multimodal variants are mostly evaluated on short-form tasks, where outputs end after a few tokens. Extending these methods to long-form generation exposes a fundamental yet underexamined limitation: token-level distillation implicitly treats all output tokens as ...
3D editing is a fundamental capability for scalable 3D content creation. While image editing has rapidly evolved toward large-scale feedforward genera...
Protein structure generative models excel at predicting single protein static structures from sequence, but routinely fail to capture the correct conf...
Background: Identifying the geographic origin of epidemic waves early is critical for targeted public health responses. Conventional statistical metho...
Tuberculosis remains a leading cause of infectious disease mortality, and the continued emergence of drug-resistant Mycobacterium tuberculosis strains...
Camouflaged object detection (COD) from a single image is a challenging task due to the high similarity between objects and their surroundings. Existi...
Estimating the precise timing of batting impact is crucial for understanding the rapid sensorimotor control. However, this task is challenging for RGB...
Foundation segmentation models such as Segment Anything Model (SAM) are now routinely used in iterative pipelines, where each predicted mask is fed ba...
Automated pavement distress assessment requires more than image-level classification or coarse bounding box detection, demanding precise localization ...
Alternative splicing of mRNA precursors is an important step in gene regulation and a major mechanism by which genetic variants cause human disease. H...
Background: Machine-learning models based on circulating biomarkers are increasingly used in cardiovascular research; however, model performance alone...
General-purpose large language models (LLMs) are trained on large corpora to acquire broad knowledge, but whether LLMs can replace, or augment, task-s...
Visual grounding, the task of localizing objects described by natural-language expressions, is a foundational capability for agricultural AI systems, ...
Distributed Image Compression (DIC) is crucial for multi-view transmission, especially when operating at extremely low bitrates (< 0.1 bpp). Its core ...
We formalize and enable the task of open tree decomposition, which segments an image into hierarchical trees of visual components with unconstrained g...
While large language models provide strong compositional reasoning, existing reasoning segmentation pipelines fail to transparently connect this reaso...
Decision trees partition the feature space using hard binary thresholds, assigning identical confidence to instances far from a decision boundary and ...
{beta}-galactosidases (BGs) are essential enzymes widely used in the food industry, particularly in the production of lactose-free products. Among the...
Motivation: Tabular-to-image methods allow convolutional neural network (CNN)-based classifiers to analyse high-dimensional biological tables by mappi...