Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
Scalable Vector Graphics (SVG) is an important image format widely adopted in graphic design because of their resolution independence and editability. The study of generating high-quality SVG has continuously drawn attention from both designers and researchers in the AIGC community. However, existing methods either produces unstructured outputs with huge computational cost or is limited to gener...
Building precise simulations of the real world and invoking numerical solvers to answer quantitative problems is an essential requirement in engineering and science. We present FEABench, a benchmark to evaluate the ability of large language models (LLMs) and LLM agents to simulate and solve physics, mathematics and engineering problems using finite element analysis (FEA). We introduce a comprehe...
Despite the span in estimating pain from facial expressions, limited works have focused on estimating the sequence-level pain, which is reported by ...
Large-scale coreference resolution presents a significant challenge in natural language processing, necessitating a balance between efficiency and a...
Objective: Zero-shot methodology promises to cut down on costs of dataset annotation and domain expertise needed to make use of NLP. Generative larg...
We propose an end-to-end trainable, cross-category method for reconstructing multiple man-made articulated objects from a single RGBD image, focusin...
Accurate and real-time three-dimensional (3D) pose estimation is challenging in resource-constrained and dynamic environments owing to its high comp...
Image retargeting aims to change the aspect-ratio of an image while maintaining its content and structure with less visual artifacts. Existing metho...
Objective: Traditional phone-based surveys are among the most accessible and widely used methods to collect biomedical and healthcare data, however,...
End-to-end autonomous driving has achieved remarkable progress by integrating perception, prediction, and planning into a fully differentiable frame...
Teleoperation plays a critical role in intuitive robot control and imitation learning, particularly for complex tasks involving mobile manipulators ...
Motivation: Building and iterating machine learning models is often a resource-intensive process. In biomedical research, scientific codebases can l...
Multimodal models integrating speech and vision hold significant potential for advancing human-computer interaction, particularly in Speech-Based Vi...
In the Edge Inference (EI) paradigm, where a Deep Neural Network (DNN) is split across the transceivers to wirelessly communicate goal-defined featu...
Reasoning before action and imagining potential outcomes (i.e., world models) are essential for embodied agents operating in complex open-world envi...
As AI technology advances, it is driving innovation across industries, increasing the demand for scalable AI project deployment. However, deployment...
To satisfy the requirements of the end-to-end fault diagnosis of gears, an integrated intelligent method of fault diagnosis for gears using accelera...
Learning from longitudinal electronic health records is limited if it does not capture the temporal trajectories of the patient's state in a clinica...
Background: Chromosome karyotype analysis is crucial for diagnosing hereditary diseases, yet detecting structural abnormalities remains challenging....
Facial Expression Recognition (FER) from videos is a crucial task in various application areas, such as human-computer interaction and health monito...