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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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ConvFormer3D-TAP: Phase/Uncertainty-Aware Front-End Fusion for Cine CMR View Classification Pipelines

Reliable recognition of standard cine cardiac MRI views is essential because each view determines wh...

STORM: End-to-End Referring Multi-Object Tracking in Videos

Referring multi-object tracking (RMOT) is a task of associating all the objects in a video that sema...

RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMs

Earth Observation (EO) systems are essentially designed to support domain experts who often express ...

VDPP: Video Depth Post-Processing for Speed and Scalability

Video depth estimation is essential for providing 3D scene structure in applications ranging from au...

TurPy: a physics-based and differentiable optical turbulence simulator for algorithmic development and system optimization

Developing optical systems for free-space applications requires simulation tools that accurately cap...

MPM: Mutual Pair Merging for Efficient Vision Transformers

Decreasing sequence length is a common way to accelerate transformers, but prior token reduction wor...

Action Images: End-to-End Policy Learning via Multiview Video Generation

World action models (WAMs) have emerged as a promising direction for robot policy learning, as they ...

TELF: An End-to-End Temporal Encoder with Late Fusion for Interpretable Disease Risk Prediction from Longitudinal Real-World Data

Deep learning models utilizing longitudinal healthcare data have significantly advanced epidemiologi...

ExploreVLA: Dense World Modeling and Exploration for End-to-End Autonomous Driving

End-to-end autonomous driving models based on Vision-Language-Action (VLA) architectures have shown ...

VOSR: A Vision-Only Generative Model for Image Super-Resolution

Most of the recent generative image super-resolution (SR) methods rely on adapting large text-to-ima...

End-to-End Shared Attention Estimation via Group Detection with Feedback Refinement

This paper proposes an end-to-end shared attention estimation method via group detection. Most previ...

Efficient Domain Adaptation for Text Line Recognition via Decoupled Language Models

Optical character recognition remains critical infrastructure for document digitization, yet state-o...

Detecting low left ventricular ejection fraction from ECG using an interpretable and scalable predictor-driven framework

Low left ventricular ejection fraction (LEF) frequently remains undetected until progression to symp...

MarkushGrapher-2: End-to-end Multimodal Recognition of Chemical Structures

Automatically extracting chemical structures from documents is essential for the large-scale analysi...

Learning to Trim: End-to-End Causal Graph Pruning with Dynamic Anatomical Feature Banks for Medical VQA

Medical Visual Question Answering (MedVQA) models often exhibit limited generalization due to relian...

End-to-end Feature Alignment: A Simple CNN with Intrinsic Class Attribution

We present Feature-Align CNN (FA-CNN), a prototype CNN architecture with intrinsic class attribution...

Towards Controllable Low-Light Image Enhancement: A Continuous Multi-illumination Dataset and Efficient State Space Framework

Low-light image enhancement (LLIE) has traditionally been formulated as a deterministic mapping. How...

Towards Real-World Document Parsing via Realistic Scene Synthesis and Document-Aware Training

Document parsing has recently advanced with multimodal large language models (MLLMs) that directly m...

MMTIT-Bench: A Multilingual and Multi-Scenario Benchmark with Cognition-Perception-Reasoning Guided Text-Image Machine Translation

End-to-end text-image machine translation (TIMT), which directly translates textual content in image...

Machine vision with small numbers of detected photons per inference

Machine vision, including object recognition and image reconstruction, is a central technology in ma...

Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving

We introduce Latent-WAM, an efficient end-to-end autonomous driving framework that achieves strong t...

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