Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
Unmanned Aerial Vehicle-based Object Detection (UAV-OD) faces substantial challenges, including small target sizes, high-density distributions, and cluttered backgrounds in UAV imagery. Current algorithms often depend on hand-crafted components like anchor boxes, which demand fine-tuning and exhibit limited generalization, and Non-Maximum Suppression (NMS), which is threshold-sensitive and prone...
6D pose estimation of rigid objects is a long-standing and challenging task in computer vision. Recently, the emergence of deep learning reveals the potential of Convolutional Neural Networks (CNNs) to predict reliable 6D poses. Given that direct pose regression networks currently exhibit suboptimal performance, most methods still resort to traditional techniques to varying degrees. For example, t...
OBJECTIVE: Machine learning algorithms can advance clinical care, including identifying mental health conditions. These algorithms are often developed...
Deep Learning in Image Registration (DLIR) methods have been tremendously successful in image registration due to their speed and ability to incorpora...
Simulation-based design, optimization, and validation of autonomous driving algorithms have proven to be crucial for their iterative improvement ove...
While personalization has been explored in traditional autonomous driving systems, it remains largely overlooked in end-to-end autonomous driving (E...
Fast diagnosis and repair of enterprise network failures is critically important since disruptions cause major business impacts. Prior works focused...
Modern methods for explainable machine learning are designed to describe how models map inputs to outputs--without deep consideration of how these e...
Solving Electromagnetic Inverse Scattering Problems (EISP) is fundamental in applications such as medical imaging, where the goal is to reconstruct ...
3D characters play a crucial role in our daily entertainment. To improve the efficiency of 3D character modeling, recent image-based methods use two...
Technological progress has led to concrete advancements in tasks that were regarded as challenging, such as automatic fact-checking. Interest in ado...
The accurate development, assessment, interpretation, and benchmarking of bioinformatics frameworks for analyzing transcriptional regulatory grammar...
Accurate interpretation of knee MRI scans relies on expert clinical judgment, often with high variability and limited scalability. Existing radiomic...
We present Sparsh-X, the first multisensory touch representations across four tactile modalities: image, audio, motion, and pressure. Trained on ~1M...
In the era of large models and big data, the security of optical fiber communication backbone networks has garnered significant attention. Quantum noi...
A novel self-adaptive secure end-to-end (E2E) transmission approach is proposed for a radio-over-fiber (RoF) system. The system integrates deep learni...
Autoregressive Transformers are increasingly being deployed as end-to-end robot and autonomous vehicle (AV) policy architectures, owing to their sca...
Multimodal chatbots have become one of the major topics for dialogue systems in both research community and industry. Recently, researchers have she...
Infrared small target detection (IRSTD) remains a long-standing challenge in complex backgrounds due to low signal-to-clutter ratios (SCR), diverse ...
End-to-end human animation with rich multi-modal conditions, e.g., text, image and audio has achieved remarkable advancements in recent years. Howev...