Latest AI and machine learning research in universal precautions for healthcare professionals.
Semantic segmentation decomposes an image into distinct mask regions corresponding to different object categories, such as people, cars, signs or buildings. Advances in machine learning (ML) have shifted this task away from traditional rule-based heuristics such as edge detection, towards deep neural networks (DNN) that learn to classify pixels directly. However, semantic segmentation DNNs crucial...
We propose Discrete Diffusion Bridges (DDB), a novel framework designed to resolve the fundamental spatiotemporal misalignment of standard discrete diffusion in image translation and generation. By corrupting data into a pure mask state via a random schedule, the conventional forward process induces a twofold misalignment: spatially, this pure-mask destination entirely discards the rich structural...
Contrastive vision-language learning uses paired chest CT volumes and radiology reports to learn abnormality classifiers without manually annotated la...
Antimicrobial peptides (AMPs) often act against multiple pathogen classes, making multi-label activity prediction a more realistic screening target th...
Antiretroviral therapy (ART) stock-outs interrupt treatment, increase the risk of virologic failure and drug resistance, and erode the population-leve...
Acinetobacter baumannii is a high priority Gram negative opportunistic pathogen known for its high rates of multidrug resistance (MDR). Minocycline (M...
Segmentation models can surpass radiologists, classification models, and vision-language models in tumor detection. Importantly, segmentation models o...
Patient-conditioned acquisition policies for ECG lead-channel selection can outperform population-wide fixed protocols by tailoring the channel budget...
Visual inspection of welded assemblies remains one of the least automated stages in many industrial production processes, still depending largely on t...
Spoken-language analysis via prompt-based domain-adaptive models is a promising direction for low-resource, non-invasive dementia screening, but such ...
Material replacement is a common interior-design operation: changing the material of a selected surface while preserving its geometry, surroundings, a...
Video games provide a scalable source of training data for video world models, offering diverse environments, complex interactions, and abundant in-th...
Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative li...
Object-centric world models forecast future videos by evolving a set of entity slots, but the variables receiving dynamics supervision are often uncon...
Referring Expression Segmentation (RES) aims to generate a pixel-level mask for the object specified by a language expression. Recent methods based on...
Generative segmentation provides an alternative to direct pixel-wise prediction by operating on learned latent representations, but effective image-to...
Promptable segmentation models provide a reusable interface, but direct transfer to automatic infrared small-target segmentation (IRSTD) exposes a mis...
AI-generated image manipulation localization identifies edited pixels, but its OOD performance lags behind image-level detection partly because pixel ...
Automated plant traits recognition from herbarium images is essential for plant sciences, yet remains challenging because background elements (e.g., t...
Omnimodal generation is central to a wide range of content creation and editing applications. In-context conditioning is essential to this paradigm. I...