Care of terminally ill / Palliative care

FAVbot: An Autonomous Target Tracking Micro-Robot with Frequency Actuation Control

Robotic autonomy at centimeter scale requires compact and miniaturization-friendly actuation integrated with sensing and neural network processing assembly within a tiny form factor. Applications of such systems have witnessed significant advancements in recent years in fields such as healthcare, manufacturing, and post-disaster rescue. The system design at this scale puts stringent constraints ...

CheapNVS: Real-Time On-Device Narrow-Baseline Novel View Synthesis

Single-view novel view synthesis (NVS) is a notorious problem due to its ill-posed nature, and often requires large, computationally expensive approaches to produce tangible results. In this paper, we propose CheapNVS: a fully end-to-end approach for narrow baseline single-view NVS based on a novel, efficient multiple encoder/decoder design trained in a multi-stage fashion. CheapNVS first approx...

PointOBB-v3: Expanding Performance Boundaries of Single Point-Supervised Oriented Object Detection

With the growing demand for oriented object detection (OOD), recent studies on point-supervised OOD have attracted significant interest. In this pap...

CHaRNet: Conditioned Heatmap Regression for Robust Dental Landmark Localization

Identifying anatomical landmarks in 3D dental models is vital for orthodontic treatment, yet manual placement is complex and time-consuming. Althoug...

FilmAgent: A Multi-Agent Framework for End-to-End Film Automation in Virtual 3D Spaces

Virtual film production requires intricate decision-making processes, including scriptwriting, virtual cinematography, and precise actor positioning...

Prediction of Lung Metastasis from Hepatocellular Carcinoma using the SEER Database

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with lung metastases being the most common site of distant spread and...

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease

Deep learning methods based on Convolutional Neural Networks (CNNs) have shown great potential to improve early and accurate diagnosis of Alzheimer'...

Self-CephaloNet: A Two-stage Novel Framework using Operational Neural Network for Cephalometric Analysis

Cephalometric analysis is essential for the diagnosis and treatment planning of orthodontics. In lateral cephalograms, however, the manual detection...

PATCHEDSERVE: A Patch Management Framework for SLO-Optimized Hybrid Resolution Diffusion Serving

The Text-to-Image (T2I) diffusion model is one of the most popular models in the world. However, serving diffusion models at the entire image level ...

DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI Reconstruction

The accelerated MRI reconstruction poses a challenging ill-posed inverse problem due to the significant undersampling in k-space. Deep neural networ...

3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene Understanding

Multi-modal Large Language Models (MLLMs) exhibit impressive capabilities in 2D tasks, yet encounter challenges in discerning the spatial positions,...

Text-to-Edit: Controllable End-to-End Video Ad Creation via Multimodal LLMs

The exponential growth of short-video content has ignited a surge in the necessity for efficient, automated solutions to video editing, with challen...

End-to-End Deep Learning for Interior Tomography with Low-Dose X-ray CT

Objective: There exist several X-ray computed tomography (CT) scanning strategies to reduce a radiation dose, such as (1) sparse-view CT, (2) low-do...

Perception-as-Control: Fine-grained Controllable Image Animation with 3D-aware Motion Representation

Motion-controllable image animation is a fundamental task with a wide range of potential applications. Recent works have made progress in controllin...

A Trust-Guided Approach to MR Image Reconstruction with Side Information

Reducing MRI scan times can improve patient care and lower healthcare costs. Many acceleration methods are designed to reconstruct diagnostic-qualit...

LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating

An up-to-date city-scale lane-level map is an indispensable infrastructure and a key enabling technology for ensuring the safety and user experience...

GIT-CXR: End-to-End Transformer for Chest X-Ray Report Generation

Medical imaging is crucial for diagnosing, monitoring, and treating medical conditions. The medical reports of radiology images are the primary medi...

Attribute-Based Robotic Grasping with Data-Efficient Adaptation

Robotic grasping is one of the most fundamental robotic manipulation tasks and has been the subject of extensive research. However, swiftly teaching...

Predicting dry matter intake in cattle at scale using gradient boosting regression techniques and Gaussian process boosting regression with Shapley additive explanation explainable artificial intelligence, MLflow, and its containerization.

Dry matter intake (DMI) is a measure critical to managing and evaluating livestock. Methods exist for quantifying individual DMI in dry lot settings t...

UAV-DETR: Efficient End-to-End Object Detection for Unmanned Aerial Vehicle Imagery

Unmanned aerial vehicle object detection (UAV-OD) has been widely used in various scenarios. However, most existing UAV-OD algorithms rely on manual...