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.

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.
Lab conducts a collaborative research project with Taichung Veterans General Hospital to Predict the Brain Tumor Growth. This research utilizes deep learning and machine learning to construct pre-processing techniques for brain tumor MRI images, as well as models for detecting the areas of brain tumors and edema. This facilitates a comparison of the extent of…
Congratulations on the remarkable achievement! Lab’s Smart System for Stress Detection in Table Tennis Athletes Win the Gold Medal Award at the 2023 World Invention Innovation Contest (WiC) in Seoul, Korea.
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…
Congratulations to Professor Meng-Hsun Tsai on receiving the Distinguished Teaching Award II from National Chung Hsing University. He stood out from many outstanding teachers in the university.
A method for managing the genetic code of species, comprising the following steps: (1) reading the genetic code sequence of species; (2) selecting a control parameter based on the length information of the genetic code sequence; (3) converting the genetic code sequence into a binary sequence using a table lookup method; (4) rearranging the binary…
Lab conducts a collaborative research project with Taichung Veterans General Hospital to predict progression-free survival in brain tumor patients. The laboratory plans to collaborate with physicians to construct a brain tumor image segmentation model to assist in the early detection and diagnosis of tumors.