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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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Task-Oriented Co-Design of Communication, Computing, and Control for Edge-Enabled Industrial Cyber-Physical Systems

This paper proposes a task-oriented co-design framework that integrates communication, computing, ...

HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder

Although end-to-end autonomous driving (E2E-AD) technologies have made significant progress in rec...

MsaMIL-Net: An End-to-End Multi-Scale Aware Multiple Instance Learning Network for Efficient Whole Slide Image Classification

Bag-based Multiple Instance Learning (MIL) approaches have emerged as the mainstream methodology f...

Reasoning in visual navigation of end-to-end trained agents: a dynamical systems approach

Progress in Embodied AI has made it possible for end-to-end-trained agents to navigate in photo-re...

CATPlan: Loss-based Collision Prediction in End-to-End Autonomous Driving

In recent years, there has been increased interest in the design, training, and evaluation of end-...

TimeLoc: A Unified End-to-End Framework for Precise Timestamp Localization in Long Videos

Temporal localization in untrimmed videos, which aims to identify specific timestamps, is crucial ...

End-to-End Action Segmentation Transformer

Existing approaches to action segmentation use pre-computed frame features extracted by methods wh...

TransParking: A Dual-Decoder Transformer Framework with Soft Localization for End-to-End Automatic Parking

In recent years, fully differentiable end-to-end autonomous driving systems have become a research...

A Map-free Deep Learning-based Framework for Gate-to-Gate Monocular Visual Navigation aboard Miniaturized Aerial Vehicles

Palm-sized autonomous nano-drones, i.e., sub-50g in weight, recently entered the drone racing scen...

An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization

Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrat...

DDCSR: A Novel End-to-End Deep Learning Framework for Cortical Surface Reconstruction from Diffusion MRI

Diffusion MRI (dMRI) plays a crucial role in studying brain white matter connectivity. Cortical su...

Generative Model-Assisted Demosaicing for Cross-multispectral Cameras

As a crucial part of the spectral filter array (SFA)-based multispectral imaging process, spectral...

Efficient End-to-end Visual Localization for Autonomous Driving with Decoupled BEV Neural Matching

Accurate localization plays an important role in high-level autonomous driving systems. Convention...

CARIL: Confidence-Aware Regression in Imitation Learning for Autonomous Driving

End-to-end vision-based imitation learning has demonstrated promising results in autonomous drivin...

Foundation Models -- A Panacea for Artificial Intelligence in Pathology?

The role of artificial intelligence (AI) in pathology has evolved from aiding diagnostics to uncov...

VDT-Auto: End-to-end Autonomous Driving with VLM-Guided Diffusion Transformers

In autonomous driving, dynamic environment and corner cases pose significant challenges to the rob...

PhenoProfiler: Advancing Phenotypic Learning for Image-based Drug Discovery

In the field of image-based drug discovery, capturing the phenotypic response of cells to various ...

ObjectVLA: End-to-End Open-World Object Manipulation Without Demonstration

Imitation learning has proven to be highly effective in teaching robots dexterous manipulation ski...

SpargeAttn: Accurate Sparse Attention Accelerating Any Model Inference

An efficient attention implementation is essential for large models due to its quadratic time comp...

VeriPlan: Integrating Formal Verification and LLMs into End-User Planning

Automated planning is traditionally the domain of experts, utilized in fields like manufacturing a...

End-to-End Chart Summarization via Visual Chain-of-Thought in Vision-Language Models

Automated chart summarization is crucial for enhancing data accessibility and enabling efficient i...

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