Latest AI and machine learning research in medical education for healthcare professionals.
With the rapid advancement of autonomous driving technology, a lack of data has become a major obstacle to enhancing perception model accuracy. Researchers are now exploring controllable data generation using world models to diversify datasets. However, previous work has been limited to studying image generation quality on specific public datasets. There is still relatively little research on ho...
The move toward open Sixth-Generation (6G) networks necessitates a novel approach to full-stack simulation environments for evaluating complex technology developments before prototyping and real-world implementation. This paper introduces an innovative approach\footnote{A lightweight, mock version of the code is available on GitHub at that combines a multi-agent framework with the Network Simula...
The rapid growth of dataset scales has been a key driver in advancing deep learning research. However, as dataset scale increases, the training proc...
Projector-camera systems (ProCams) simulation aims to model the physical project-and-capture process and associated scene parameters of a ProCams, a...
Evolutionary Computation (EC) often throws away learned knowledge as it is reset for each new problem addressed. Conversely, humans can learn from sma...
Abdominal aortic aneurysms (AAAs) are localized dilatations of the abdominal aorta that can lead to life-threatening rupture if left untreated. AAAs...
Roadside Collaborative Perception refers to a system where multiple roadside units collaborate to pool their perceptual data, assisting vehicles in ...
The cloud computing model enables the on-demand provisioning of computing resources, reducing manual management, increasing efficiency, and improvin...
Neural reconstruction models for autonomous driving simulation have made significant strides in recent years, with dynamic models becoming increasin...
Magnetic soft continuum robots (MSCRs) have emerged as a promising technology for minimally invasive interventions, offering enhanced dexterity and ...
Ensuring the safety of autonomous vehicles necessitates comprehensive simulation of multi-sensor data, encompassing inputs from both cameras and LiD...
With the advent of deep learning, expression recognition has made significant advancements. However, due to the limited availability of annotated co...
The precision, stability, and performance of lightweight high-strength steel structures in heavy machinery is affected by their highly nonlinear dyn...
The growing use of technology in K--8 classrooms highlights a parallel need for formal learning opportunities aimed at helping children use technolo...
Computer programming represents a rapidly evolving and sought-after career path in the 21st century. Nevertheless, novice learners may find the proc...
We present MagicInfinite, a novel diffusion Transformer (DiT) framework that overcomes traditional portrait animation limitations, delivering high-f...
Robotic assembly remains a significant challenge due to complexities in visual perception, functional grasping, contact-rich manipulation, and perfo...
Large Language Models excel in reasoning yet often rely on Chain-of-Thought prompts, limiting performance on tasks demanding more nuanced topologica...
In recent years, the emergence of deep convolutional neural networks has positioned face recognition as a prominent research focus in computer visio...
We present a transformer model, named DeepHalo, to predict the occurrence of halo coronal mass ejections (CMEs). Our model takes as input an active ...