AIMC Topic: Computer Graphics

Clear Filters Showing 11 to 20 of 233 articles

Hit Around: Substitutional Moving Robot for Immersive and Exertion Interaction with Encountered-Type Haptic.

IEEE transactions on visualization and computer graphics
Previous works have shown the potential of immersive technologies to make physical activities a more engaging experience. With encountered-type haptic feedback, users can perceive a more realistic sensation for exertion interaction in substitutions r...

Enhancing Patient Acceptance of Robotic Ultrasound through Conversational Virtual Agent and Immersive Visualizations.

IEEE transactions on visualization and computer graphics
Robotic ultrasound systems have the potential to improve medical diagnostics, but patient acceptance remains a key challenge. To address this, we propose a novel system that combines an AI-based virtual agent, powered by a large language model (LLM),...

Pair-wise or high-order? A self-adaptive graph framework for knowledge graph embedding.

Neural networks : the official journal of the International Neural Network Society
Knowledge graphs (KGs) depict entities as nodes and connections as edges, and they are extensively utilized in numerous artificial intelligence applications. However, knowledge graphs often suffer from incompleteness, which seriously affects downstre...

A graph neural network explainability strategy driven by key subgraph connectivity.

Journal of biomedical informatics
Current explainability strategies for Graph Neural Networks (GNNs) often focus on individual nodes or edges, neglecting the significance of key subgraphs in decision-making processes. This limitation can result in dispersed and less reliable explanat...

Large Language Model-Driven 3D Hyper-Realistic Interactive Intelligent Digital Human System.

Sensors (Basel, Switzerland)
Digital technologies are undergoing comprehensive integration across diverse domains and processes of the human economy, politics, culture, society, and ecological civilization. This integration brings forth novel concepts, formats, and models. In th...

Disentangled Active Learning on Graphs.

Neural networks : the official journal of the International Neural Network Society
Active learning on graphs (ALG) has emerged as a compelling research field due to its capacity to address the challenge of label scarcity. Existing ALG methods incorporate diversity into their query strategies to maximize the gains from node sampling...

Learning Pose Controllable Human Reconstruction With Dynamic Implicit Fields From a Single Image.

IEEE transactions on visualization and computer graphics
Recovering a user-special and controllable human model from a single RGB image is a nontrivial challenge. Existing methods usually generate static results with an image consistent subject's pose. Our work aspires to achieve pose-controllable human re...

A GPU-accelerated fuzzy method for real-time CT volume filtering.

PloS one
During acquisition and reconstruction, medical images may become noisy and lose diagnostic quality. In the case of CT scans, obtaining less noisy images results in a higher radiation dose being administered to the patient. Filtering techniques can be...

DropNaE: Alleviating irregularity for large-scale graph representation learning.

Neural networks : the official journal of the International Neural Network Society
Large-scale graphs are prevalent in various real-world scenarios and can be effectively processed using Graph Neural Networks (GNNs) on GPUs to derive meaningful representations. However, the inherent irregularity found in real-world graphs poses cha...

PhenoFlow: A Human-LLM Driven Visual Analytics System for Exploring Large and Complex Stroke Datasets.

IEEE transactions on visualization and computer graphics
Acute stroke demands prompt diagnosis and treatment to achieve optimal patient outcomes. However, the intricate and irregular nature of clinical data associated with acute stroke, particularly blood pressure (BP) measurements, presents substantial ob...