Participate in the 2024 GCBME & TSBE Annual Meeting at NCKU
Our lab participated in the 2024 GCBME and TSBE Annual Meeting held at National Cheng Kung University, exploring the application of deep learning techniques in the field of sports science.
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Dr. Tsai’s Patent Application Has Been Approved! An Improved Decompressed Image Methodology
This invention provides an improved vector quantization encoding for image quality restoration and a fast codebook training method. The invention divides image blocks into multiple data groups, and trains Cg encoding words for each group based on the standard deviation and data quantity of each group. The invention effectively enhances compressed image quality and significantly…
Farewell Party for Fu-Sheng Hsueh, Yu-Sheng Cheng, Min-Yu Chen, Yen-Chih Feng, Wen-Chieh Li, Chia-Hsien Li, and Yen-Chun Lu
Farewell Party for Fu-Sheng Hsueh, Yu-Sheng Cheng, Min-Yu Chen, Yen-Chih Feng, Wen-Chieh Li, Chia-Hsien Li, and Yen-Chun Lu! Wishing everyone to become extraordinary ordinary individuals on their future life journey.
Lab’s Semester Gathering
The laboratory’s semester gathering at ‘Eatogether’ restaurant. To celebrate the graduation of our seniors and to wish our juniors all the best in their future endeavors. Let’s enjoy our time together to the fullest.
Dr. Meng-Hsiun Tsai Receives Sports Science Research Grant 2024 by the Sports Administration
Dr. Meng-Hsiun Tsai has long been dedicated to research in sports science and artificial intelligence, achieving outstanding results in areas such as athlete stress detection, fatigue monitoring, and sports injury prevention.
Dr. Meng-Hsiun Tsai Presents the Works at MOE Teaching Practice Research Program Workshop
Dr. Meng-Hsiun Tsai Presents the works (directed by Ying-Chen Lin, Chung-Ting Lin, Fu-Sheng Hsueh, and Keng-Yuan Nien) at MOE Teaching Practice Research Program Workshop! The professor demonstrated how to enable learners to interact with big data in a virtual 3D environment.
Lab Conducts a Collaborative Research Project with CCH to Predict the Prognosis and Healthcare Consumption of Hospitalized Trauma Patients
Lab Conducts a collaborative research project with Changhua Christian Hospital to predict the prognosis and healthcare consumption of hospitalized trauma patients. The project introduces deep learning for predicting in-hospital mortality and length of stay for patients. Therefore, it contributes to predicting the prognosis and healthcare consumption of hospitalized trauma patients, ultimately enhancing the quality of…
