Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
We propose a feed-forward Gaussian Splatting model that unifies 3D scene and semantic field reconstruction. Combining 3D scenes with semantic fields facilitates the perception and understanding of the surrounding environment. However, key challenges include embedding semantics into 3D representations, achieving generalizable real-time reconstruction, and ensuring practical applicability by using...
The continuous improvements on image compression with variational autoencoders have lead to learned codecs competitive with conventional approaches in terms of rate-distortion efficiency. Nonetheless, taking the quantization into account during the training process remains a problem, since it produces zero derivatives almost everywhere and needs to be replaced with a differentiable approximation...
End-to-end autonomous driving has emerged as a dominant paradigm, yet its highly entangled black-box models pose significant challenges in terms of ...
End-to-end multi-modal planning is a promising paradigm in autonomous driving, enabling decision-making with diverse trajectory candidates. A key co...
In complex driving environments, autonomous vehicles must navigate safely. Relying on a single predicted path, as in regression-based approaches, us...
A central challenge in modern language models (LMs) is intrinsic hallucination: the generation of information that is plausible but unsubstantiated ...
Image matching, which establishes correspondences between two-view images to recover 3D structure and camera geometry, serves as a cornerstone in co...
The detection of ligand binding sites for proteins is a fundamental step in Structure-Based Drug Design. Despite notable advances in recent years, e...
When developing control laws for robotic systems, the principle factor when examining their performance is choosing inputs that allow smooth trackin...
Pre-trained encoders for offline feature extraction followed by multiple instance learning (MIL) aggregators have become the dominant paradigm in co...
In recent years, federated learning (FL) has made significant advance in privacy-sensitive applications. However, it can be hard to ensure that FL p...
Spatial intelligence, encompassing 3D reconstruction, perception, and reasoning, is fundamental to applications such as robotics, aerial imaging, an...
Spatial intelligence, encompassing 3D reconstruction, perception, and reasoning, is fundamental to applications such as robotics, aerial imaging, an...
Operations research (OR) is widely deployed to solve critical decision-making problems with complex objectives and constraints, impacting manufactur...
Blood cell detection is an important part of medical diagnosis. Object detection is trending for blood cell analysis, with research focusing on high-p...
With the rapid penetration of artificial intelligence across industries and scenarios, a key challenge in building the next-generation intelligent c...
On-device learning at the edge enables low-latency, private personalization with improved long-term robustness and reduced maintenance costs. Yet, a...
Urban design is a multifaceted process that demands careful consideration of site-specific constraints and collaboration among diverse professionals...
Can your humanoid walk up and hand you a full cup of beer, without spilling a drop? While humanoids are increasingly featured in flashy demos like d...
The latest advancements in multi-modal large language models (MLLMs) have spurred a strong renewed interest in end-to-end motion planning approaches...