Latest AI and machine learning research in medical education for healthcare professionals.
Surgical simulation offers a promising addition to conventional surgical training. However, available simulation tools lack photorealism and rely on hardcoded behaviour. Denoising Diffusion Models are a promising alternative for high-fidelity image synthesis, but existing state-of-the-art conditioning methods fall short in providing precise control or interactivity over the generated scenes. W...
As artificial intelligence (AI) technologies begin to permeate diverse fields-from healthcare to education-consumers, researchers and policymakers are increasingly raising concerns about whether and how AI is regulated. It is therefore reasonable to anticipate that alignment with principles of 'ethical' or 'responsible' AI, as well as compliance with law and policy, will form an increasingly imp...
Critical infrastructures face demanding challenges due to natural and human-generated threats, such as pandemics, workforce shortages or cyber-attac...
This paper proposes a vision-in-the-loop simulation environment for deep monocular pose estimation of a UAV operating in an ocean environment. Recen...
Modeling humans in physical scenes is vital for understanding human-environment interactions for applications involving augmented reality or assessm...
Graph generation is a critical yet challenging task as empirical analyses require a deep understanding of complex, non-Euclidean structures. Althoug...
The Human Cognitive Simulation Framework represents a significant advancement in integrating human cognitive capabilities into artificial intelligen...
Recent advances in large models have significantly advanced image-to-3D reconstruction. However, the generated models are often fused into a single ...
Robot learning requires a considerable amount of high-quality data to realize the promise of generalization. However, large data sets are costly to ...
In this work, we present INTACT, a novel two-phase framework designed to enhance the robustness of deep neural networks (DNNs) against noisy LiDAR d...
Simulations and bisimulations are ubiquitous in the study of concurrent systems and modal logics of various types. Besides classical relational tran...
Model order reduction (MOR) involves offering low-dimensional models that effectively approximate the behavior of complex high-order systems. Due to...
The advancement of large language models (LLMs) has opened new frontiers in natural language processing, particularly in specialized domains like he...
Cutting thin-walled deformable structures is common in daily life, but poses significant challenges for simulation due to the introduced spatial dis...
Image denoising algorithms have been extensively investigated for medical imaging. To perform image denoising, penalized least-squares (PLS) problem...
Current medical AI systems often fail to replicate real-world clinical reasoning, as they are predominantly trained and evaluated on static text and...
The classification and recognition of maritime objects are crucial for enhancing maritime safety, monitoring, and intelligent sea environment predic...
The ability to accomplish tasks via natural language instructions is one of the most efficient forms of interaction between humans and technology. T...
Reproducibility of computational research is critical for ensuring transparency, reliability and reusability. Challenges with computational reproduc...
While learning personalization offers great potential for learners, modern practices in higher education require a deeper consideration of domain mo...