Latest AI and machine learning research in medical education for healthcare professionals.
Aiming at the problems of poor quality of steganographic images and slow network convergence of im...
In computer animation, game design, and human-computer interaction, synthesizing human motion that...
In recent years, a large number of works have introduced Convolutional Neural Networks (CNNs) into...
This paper introduces the Cable Robot Simulation and Control (CaRoSaC) Framework, which integrates...
Diffusion models have become central to various image editing tasks, yet they often fail to fully ...
Physics driven image simulation allows for the modeling and creation of realistic imagery beyond w...
Background: Automated classification of thyroid Fine Needle Aspiration Biopsy (FNAB) images faces ...
High-fidelity simulation is essential for robotics research, enabling safe and efficient testing o...
Object detection in satellite-borne Synthetic Aperture Radar (SAR) imagery holds immense potential...
Tactile sensing is crucial for achieving human-level robotic capabilities in manipulation tasks. V...
This paper explores optimal data selection strategies for Reinforcement Learning with Verified Rew...
The role of mental simulation in human physical reasoning is widely acknowledged, but whether it i...
Recent advances in visual synthesis have leveraged diffusion models and attention mechanisms to ac...
Restoring severely blurred images remains a significant challenge in computer vision, impacting ap...
Digital images of Chinas maps play a crucial role in map detection, particularly in ensuring natio...
Large-scale egocentric video datasets capture diverse human activities across a wide range of scen...
Large Language Models (LLMs) have significantly advanced smart education in the Artificial General...
Beamforming is a key technology in millimeter-wave (mmWave) communications that improves signal tr...
The complexity and scale of Volumetric and Simulation datasets for Scientific Visualization(SciVis...
In this paper, we tackle the problem of Generalized Category Discovery (GCD). Given a dataset cont...
Conventional Vision Transformer simplifies visual modeling by standardizing input resolutions, oft...