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Care of terminally ill / Palliative care

Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.

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SPECI: Skill Prompts based Hierarchical Continual Imitation Learning for Robot Manipulation

Real-world robot manipulation in dynamic unstructured environments requires lifelong adaptability to evolving objects, scenes and tasks. Traditional imitation learning relies on static training paradigms, which are ill-suited for lifelong adaptation. Although Continual Imitation Learnin (CIL) enables incremental task adaptation while preserving learned knowledge, current CIL methods primarily ov...

SCALE-Sim v3: A modular cycle-accurate systolic accelerator simulator for end-to-end system analysis

The rapid advancements in AI, scientific computing, and high-performance computing (HPC) have driven the need for versatile and efficient hardware accelerators. Existing tools like SCALE-Sim v2 provide valuable cycle-accurate simulations for systolic-array-based architectures but fall short in supporting key modern features such as sparsity, multi-core scalability, and comprehensive memory analy...

FLARE: Feature-based Lightweight Aggregation for Robust Evaluation of IoT Intrusion Detection

The proliferation of Internet of Things (IoT) devices has expanded the attack surface, necessitating efficient intrusion detection systems (IDSs) fo...

End-Edge Model Collaboration: Bandwidth Allocation for Data Upload and Model Transmission

The widespread adoption of large artificial intelligence (AI) models has enabled numerous applications of the Internet of Things (IoT). However, lar...

Transforming Hyperspectral Images Into Chemical Maps: An End-to-End Deep Learning Approach

Current approaches to chemical map generation from hyperspectral images are based on models such as partial least squares (PLS) regression, generati...

Compile Scene Graphs with Reinforcement Learning

Next-token prediction is the fundamental principle for training large language models (LLMs), and reinforcement learning (RL) further enhances their...

Compile Scene Graphs with Reinforcement Learning

Next-token prediction is the fundamental principle for training large language models (LLMs), and reinforcement learning (RL) further enhances their...

Putting the Segment Anything Model to the Test with 3D Knee MRI - A Comparison with State-of-the-Art Performance

Menisci are cartilaginous tissue found within the knee that contribute to joint lubrication and weight dispersal. Damage to menisci can lead to onse...

AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Industrial Anomaly Detection (IAD) poses a formidable challenge due to the scarcity of defective samples, making it imperative to deploy models capa...

Flying Hand: End-Effector-Centric Framework for Versatile Aerial Manipulation Teleoperation and Policy Learning

Aerial manipulation has recently attracted increasing interest from both industry and academia. Previous approaches have demonstrated success in var...

SemiETS: Integrating Spatial and Content Consistencies for Semi-Supervised End-to-end Text Spotting

Most previous scene text spotting methods rely on high-quality manual annotations to achieve promising performance. To reduce their expensive costs,...

Mixture-of-Shape-Experts (MoSE): End-to-End Shape Dictionary Framework to Prompt SAM for Generalizable Medical Segmentation

Single domain generalization (SDG) has recently attracted growing attention in medical image segmentation. One promising strategy for SDG is to leve...

Localization Meets Uncertainty: Uncertainty-Aware Multi-Modal Localization

Reliable localization is critical for robot navigation in complex indoor environments. In this paper, we propose an uncertainty-aware localization m...

Adaptive Vision-Guided Robotic Arm Control for Precision Pruning in Dynamic Orchard Environments

This study presents a vision-guided robotic control system for automated fruit tree pruning applications. Traditional agricultural practices rely on...

SIGMAN:Scaling 3D Human Gaussian Generation with Millions of Assets

3D human digitization has long been a highly pursued yet challenging task. Existing methods aim to generate high-quality 3D digital humans from sing...

The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data

Differentially Private (DP) generative marginal models are often used in the wild to release synthetic tabular datasets in lieu of sensitive data wh...

SVG-IR: Spatially-Varying Gaussian Splatting for Inverse Rendering

Reconstructing 3D assets from images, known as inverse rendering (IR), remains a challenging task due to its ill-posed nature. 3D Gaussian Splatting...

End2end-ALARA: Approaching the ALARA Law in CT Imaging with End-to-end Learning

Computed tomography (CT) examination poses radiation injury to patient. A consensus performing CT imaging is to make the radiation dose as low as re...

RAMBO: RL-augmented Model-based Optimal Control for Whole-body Loco-manipulation

Loco-manipulation -- coordinated locomotion and physical interaction with objects -- remains a major challenge for legged robots due to the need for...

PosterMaker: Towards High-Quality Product Poster Generation with Accurate Text Rendering

Product posters, which integrate subject, scene, and text, are crucial promotional tools for attracting customers. Creating such posters using moder...

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