By using the machine learning algorithms, this study developed a risk stratification model for predicting the occurrence of in-hospital cardiac arrest (IHCA) events in patients admitted from the em...
With our autonomous UAV systems, we can effectively reduce many high-risk and high-cost inspections which require high manpower, such as inspections of dams, river, coastline patrols, etc.. Operato...
This project proposes a learning from demonstration (LfD) system that allows robots to be not only taught by human via demonstration but also adjusted by themselves
According to the World Health Organization statistics, hypertension is the number one attributable cause of death. Pulse wave velocity (PWV) is a well-known measure of long-term blood pressure burd...
The application of voice assistants is becoming more and more popular, however, due to the inefficiency of artificial intelligence-based technology, current products are mostly built by using rules...
We have proposed in this project the first time series classification technique that considers accuracy, earliness, and varied lengths simultaneously, containing a novel deep reinforcement learning...
The project is to establish an AUV system capable of performing underwater exploration and ecological surveys in various shallow water areas over a long period. This system can automate the collect...
The NeRF-based technique describes a super-fast convergence approach to reconstructing the per-scene radiance field from a set of images that capture the scene with known poses.
This project develops a high-performance end-to-end reinforcement learning training platform for autonomous miniature car racing. With this platform, our team won the championship of Amazon DeepRac...
With the maturity of deep learning technology, reading comprehension model (given an article and a question, the AI model automatically finds the answer to the question from the article) has become...