Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
Training-free guided generation is a widely used and powerful technique that allows the end user to exert further control over the generative process of flow/diffusion models. Generally speaking, two families of techniques have emerged for solving this problem for gradient-based guidance: namely, posterior guidance (i.e., guidance via projecting the current sample to the target distribution via ...
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...
Fingerprint localization has gained significant attention due to its cost-effective deployment, low complexity, and high efficacy. However, traditio...
Dense object detection is widely used in automatic driving, video surveillance, and other fields. This paper focuses on the challenging task of dens...
Neural networks (NNs), with their powerful nonlinear mapping and end-to-end capabilities, are widely applied in mechanical intelligent fault diagnos...
Crafting magic and illusions is one of the most thrilling aspects of filmmaking, with visual effects (VFX) serving as the powerhouse behind unforget...
Current video-based Masked Autoencoders (MAEs) primarily focus on learning effective spatiotemporal representations from a visual perspective, which...
This study investigates the performance of various large language models (LLMs) on zero-shot end-to-end relation extraction (RE) in Chinese, a task ...
Computational models of atrial electrophysiology (EP) are increasingly utilized for applications such as the development of advanced mapping systems...
Objective: To evaluate the accuracy, computational cost and portability of a new Natural Language Processing (NLP) method for extracting medication ...
Autonomous edge computing in robotics, smart cities, and autonomous vehicles relies on the seamless integration of sensing, processing, and actuatio...
We propose ReMiDi, a novel method for inferring neuronal microstructure as arbitrary 3D meshes using a differentiable diffusion Magnetic Resonance I...
Text-to-Image (T2I) synthesis is a challenging task that requires modeling complex interactions between two modalities ( i.e., text and image). A co...
End-to-end human animation, such as audio-driven talking human generation, has undergone notable advancements in the recent few years. However, exis...
Visual speech recognition remains an open research problem where different challenges must be considered by dispensing with the auditory sense, such...
Though end-to-end speech-to-text translation has been a great success, we argue that the cascaded speech-to-text translation model still has its pla...
Image animation has become a promising area in multimodal research, with a focus on generating videos from reference images. While prior work has la...
Functional data - observations in the form of curves or trajectories - arise in diverse domains such as biomedical sensing, motion capture, and hand...
This paper presents Contourformer, a real-time contour-based instance segmentation algorithm. The method is fully based on the DETR paradigm and ach...
There has been substantial progress in humanoid robots, with new skills continuously being taught, ranging from navigation to manipulation. While th...