Latest AI and machine learning research in covid-19 for healthcare professionals.
To advance real-world fashion image editing, we analyze existing two-stage pipelines(mask generation followed by diffusion-based editing)which overly prioritize generator optimization while neglecting mask controllability. This results in two critical limitations: I) poor user-defined flexibility (coarse-grained human masks restrict edits to predefined regions like upper torso; fine-grained clot...
Transformers have become the de facto standard for a wide range of tasks, from image classification to physics simulations. Despite their impressive performance, the quadratic complexity of standard Transformers in both memory and time with respect to the input length makes them impractical for processing high-resolution inputs. Therefore, several variants have been proposed, the most successful...
Therapeutic antibodies require not only high-affinity target engagement, but also favorable manufacturability, stability, and safety profiles for cl...
Antibody engineering is essential for developing therapeutics and advancing biomedical research. Traditional discovery methods often rely on time-co...
The standard enthalpy of formation (Δ°) is a fundamental thermodynamic property that is essential for understanding various physicochemical processes....
Instance segmentation of novel objects instances in RGB images, given some example images for each object, is a well known problem in computer visio...
Document shadow removal is a crucial task in the field of document image enhancement. However, existing methods tend to remove shadows with constant...
Understanding the vast noncoding cancer genome requires cutting-edge, high-resolution, and accessible strategies. Artificial intelligence is revolutio...
We introduce and validate the lottery codec hypothesis, which states that untrained subnetworks within randomly initialized networks can serve as sy...
Text-to-image generation has greatly advanced content creation, yet accurately rendering visual text remains a key challenge due to blurred glyphs, ...
Due to its invariance to rigid transformations such as rotations and reflections, Procrustes-Wasserstein (PW) was introduced in the literature as an...
Introduction: Deep learning (DL) models can help detect intracranial aneurysms on CTA, but high false positive (FP) rates remain a barrier to clinic...
Recent advancements in deep learning for medical image segmentation are often limited by the scarcity of high-quality training data.While diffusion ...
Region of Interest (ROI)-based image compression optimizes bit allocation by prioritizing ROI for higher-quality reconstruction. However, as the use...
Six-degree-of-freedom robotic testing is used to gain insight into knee function by measuring the biomechanics of cadaveric knees. However, it can be ...
Background: Sepsis-associated acute kidney injury (SA-AKI) is a life-threatening complication with mortality rates exceeding 50%, yet its molecular dr...
Discrete wavelet transforms have been applied in many machine learning models for the analysis of COVID-19; however, little is known about the impact ...
Cellular senescence is a complex biological process with a dual role in tissue homeostasis and aging-related pathologies. Accumulation of senescent ce...
The present study aimed to develop and validate a fusion model based on multi-phase contrast-enhanced computed tomography (CECT) radiomics features co...
PURPOSE: Noninvasive, accurate and novel approaches to predict patients who will achieve pathological complete response (pCR) after neoadjuvant chemot...