Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
Crop row detection is essential for enabling autonomous navigation in GPS-denied environments, such as under-canopy agricultural settings. Traditional methods often struggle with occlusions, variable lighting conditions, and the structural variability of crop rows. To address these challenges, RowDetr, a novel end-to-end neural network architecture, is introduced for robust and efficient row det...
Vision-based autonomous driving shows great potential due to its satisfactory performance and low costs. Most existing methods adopt dense representations (e.g., bird's eye view) or sparse representations (e.g., instance boxes) for decision-making, which suffer from the trade-off between comprehensiveness and efficiency. This paper explores a Gaussian-centric end-to-end autonomous driving (Gauss...
DNN-based watermarking methods have rapidly advanced, with the ``Encoder-Noise Layer-Decoder'' (END) framework being the most widely used. To ensure...
End-to-end optimization, which simultaneously optimizes optics and algorithms, has emerged as a powerful data-driven method for computational imagin...
End-to-end autonomous driving has received increasing attention due to its potential to learn from large amounts of data. However, most existing met...
In recent years, Multimodal Large Language Models (MLLM) have achieved notable advancements, demonstrating the feasibility of developing an intellig...
Image retrieval methods rely on metric learning to train backbone feature extraction models that can extract discriminant queries and reference (gal...
Recently, we have witnessed the rise of novel ``event-based'' camera sensors for high-speed, low-power video capture. Rather than recording discrete...
Large-scale 3D point clouds (LS3DPC) obtained by LiDAR scanners require huge storage space and transmission bandwidth due to a large amount of data....
Arbitrary Style Transfer (AST) achieves the rendering of real natural images into the painting styles of arbitrary art style images, promoting art c...
We present the first loss agent, dubbed LossAgent, for low-level image processing tasks, e.g., image super-resolution and restoration, intending to ...
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...
As a sensitive functional imaging technique, positron emission tomography (PET) plays a critical role in early disease diagnosis. However, obtaining...
In the fifth-generation (5G) era, eliminating communication interference sources is crucial for maintaining network performance. Interference often ...
Understanding video content is pivotal for advancing real-world applications like activity recognition, autonomous systems, and human-computer inter...
Motion control is crucial for generating expressive and compelling video content; however, most existing video generation models rely mainly on text...
This paper aims to bring fine-grained expression control while maintaining high-fidelity identity in portrait generation. This is challenging due to...
The adoption of Vision Transformers (ViTs) in resource-constrained applications necessitates improvements in inference throughput. To this end sever...
Due to network operation and maintenance relying heavily on network traffic monitoring, traffic matrix analysis has been one of the most crucial iss...
Recent advances in imitation learning have shown significant promise for robotic control and embodied intelligence. However, achieving robust genera...