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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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VRVVC: Variable-Rate NeRF-Based Volumetric Video Compression

Neural Radiance Field (NeRF)-based volumetric video has revolutionized visual media by delivering photorealistic Free-Viewpoint Video (FVV) experiences that provide audiences with unprecedented immersion and interactivity. However, the substantial data volumes pose significant challenges for storage and transmission. Existing solutions typically optimize NeRF representation and compression indep...

Uni-AdaFocus: Spatial-temporal Dynamic Computation for Video Recognition

This paper presents a comprehensive exploration of the phenomenon of data redundancy in video understanding, with the aim to improve computational efficiency. Our investigation commences with an examination of spatial redundancy, which refers to the observation that the most informative region in each video frame usually corresponds to a small image patch, whose shape, size and location shift sm...

Efficient Adaptation of Multilingual Models for Japanese ASR

This study explores fine-tuning multilingual ASR (Automatic Speech Recognition) models, specifically OpenAI's Whisper-Tiny, to improve performance i...

RowDetr: End-to-End Row Detection Using Polynomials

Crop row detection is essential for enabling autonomous navigation in GPS-denied environments, such as under-canopy agricultural settings. Tradition...

GaussianAD: Gaussian-Centric End-to-End Autonomous Driving

Vision-based autonomous driving shows great potential due to its satisfactory performance and low costs. Most existing methods adopt dense represent...

END$^2$: Robust Dual-Decoder Watermarking Framework Against Non-Differentiable Distortions

DNN-based watermarking methods have rapidly advanced, with the ``Encoder-Noise Layer-Decoder'' (END) framework being the most widely used. To ensure...

A Differentiable Wave Optics Model for End-to-End Computational Imaging System Optimization

End-to-end optimization, which simultaneously optimizes optics and algorithms, has emerged as a powerful data-driven method for computational imagin...

Doe-1: Closed-Loop Autonomous Driving with Large World Model

End-to-end autonomous driving has received increasing attention due to its potential to learn from large amounts of data. However, most existing met...

Towards a Multimodal Large Language Model with Pixel-Level Insight for Biomedicine

In recent years, Multimodal Large Language Models (MLLM) have achieved notable advancements, demonstrating the feasibility of developing an intellig...

Image Retrieval Methods in the Dissimilarity Space

Image retrieval methods rely on metric learning to train backbone feature extraction models that can extract discriminant queries and reference (gal...

Low-Latency Scalable Streaming for Event-Based Vision

Recently, we have witnessed the rise of novel ``event-based'' camera sensors for high-speed, low-power video capture. Rather than recording discrete...

Compression of Large-Scale 3D Point Clouds Based on Joint Optimization of Point Sampling and Feature Extraction

Large-scale 3D point clouds (LS3DPC) obtained by LiDAR scanners require huge storage space and transmission bandwidth due to a large amount of data....

StyleMark: A Robust Watermarking Method for Art Style Images Against Black-Box Arbitrary Style Transfer

Arbitrary Style Transfer (AST) achieves the rendering of real natural images into the painting styles of arbitrary art style images, promoting art c...

LossAgent: Towards Any Optimization Objectives for Image Processing with LLM Agents

We present the first loss agent, dubbed LossAgent, for low-level image processing tasks, e.g., image super-resolution and restoration, intending to ...

End to End Collaborative Synthetic Data Generation

The success of AI is based on the availability of data to train models. While in some cases a single data custodian may have sufficient data to enab...

End-to-end Triple-domain PET Enhancement: A Hybrid Denoising-and-reconstruction Framework for Reconstructing Standard-dose PET Images from Low-dose PET Sinograms

As a sensitive functional imaging technique, positron emission tomography (PET) plays a critical role in early disease diagnosis. However, obtaining...

Real-Time AIoT for UAV Antenna Interference Detection via Edge-Cloud Collaboration

In the fifth-generation (5G) era, eliminating communication interference sources is crucial for maintaining network performance. Interference often ...

Temporally Consistent Dynamic Scene Graphs: An End-to-End Approach for Action Tracklet Generation

Understanding video content is pivotal for advancing real-world applications like activity recognition, autonomous systems, and human-computer inter...

EmojiDiff: Advanced Facial Expression Control with High Identity Preservation in Portrait Generation

This paper aims to bring fine-grained expression control while maintaining high-fidelity identity in portrait generation. This is challenging due to...

Token Cropr: Faster ViTs for Quite a Few Tasks

The adoption of Vision Transformers (ViTs) in resource-constrained applications necessitates improvements in inference throughput. To this end sever...

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