Latest AI and machine learning research in work force for healthcare professionals.
A major challenge in finger vein recognition is the lack of large-scale public datasets. Existing datasets contain few identities and limited samples per finger, restricting the advancement of deep learning-based methods. To address this, we propose FVeinSyn, a large-scale controllable synthetic data generation framework for finger vein. It explicitly decouples synthesis of vascular topology and i...
Neural network training has an oracle problem: a run can converge normally and yield a usable model while the software beneath it computes something other than specified. Almost all such work runs on one stack, so there is rarely anything independent to check against. We study whether independently implemented training stacks can serve as differential oracles for a whole fine-tuning pipeline, rath...
Assembly and disassembly processes rely on expert knowledge that is difficult to document, reuse, and transfer. This paper presents a data-centric app...
Recent Visual-Language Models (VLMs) have enhanced the capabilities of pre-trained LLMs by adding vision tokens alongside text, with approaches like L...
Modern mental healthcare faces a critical shortage of senior supervisory oversight, leading to a "supervision gap" where novice therapists manage high...
Small-scale image classification is often limited by the scarcity of training data. Generative data augmentation (GDA) based on pretrained generative ...
Despite the rapid industrialization of the touch sensor manufacturing process, most of these sensors are still handmade in research laboratories. This...
Live game commentary is scarce: it exists for professional esports broadcasts and almost nowhere else. We present a content-based video narration syst...
Text-to-image generation has reached photorealistic quality, yet state-of-the-art systems remain unreliable at producing scientific diagrams, whose va...
Vision-Language Models (VLMs) are highly effective in retrieving semantically relevant images. However, in practice, relevance alone is often insuffic...
Automated radiology report generation is advancing rapidly in response to the shortage of radiologists, yet unlike a perception model, existing genera...
Despite rapid advances in generative models, achieving pixel-level precision in sketch-based image editing remains a persistent challenge, particularl...
Audio-visual interaction is the standard for patient-physician consultations, enabling natural communication and effective assessment of illness throu...
Foodborne pathogens including Salmonella spp., Escherichia coli and Listeria monocytogenes cause an estimated 600 million illnesses annually. Yet conv...
Engineered Skeletal Muscle Tissues (ESMs) have become a key structure for biomedical disease modeling and pharmacological screening, yet their functio...
This paper proposes an automated classification method of chest CT volumes based on likelihood of COVID-19 cases. Novel coronavirus disease 2019 (COVI...
This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID...
Background and Objective: Generating realistic medical images with anatomically accurate segmentation masks helps address the shortage of annotated da...
Background: Healthcare has witnessed administrative staffing roles balloon to twice the number of employed clinicians, resulting in $950 billion per y...
Generation in video diffusion or flow models is computationally expensive due to the slow and iterative sampling process. Current state-of-the-art (SO...