[20191129 : Colloquium]
High-performance, Learning-based Visual Computing for Large-scale
1. 일시 : 2019년 11월 29일 (금) 오후 4시 30분 ~ 5시 30분
2. 장소 : 아산이학관 526호
3. 연사 : 정원기(울산과학기술원 전기전자컴퓨터공학부, 교수)
4. 제목 : High-performance, Learning-based Visual Computing for Large-scale
Biomedical Image Analysis
5. 내용 : High-resolution, large-scale image data play a central role in biomedical researches, but they also pose very challenging computational problems for image processing and visualization in terms of developing suitable algorithms, coping with the ever-increasingdata sizes, and maintaining interactive performance. Massively parallel computing systems, such as graphics processing units and distributed cluster systems, can be a solution for such computation-demanding tasks due to its scalable and parallel architecture.In addition, recent advances in machine learning can be another solution because the learning-based approach can accelerate computation by shifting the time-consuming computing process into the training (pre-processing) phase and reducing prediction time byperforming only one-pass deployment of a feed-forward neural network. In this talk, I will introduce several examples of such research directions from our recent development on large-scale biomedical image analysis using high-performance computing and machinelearning techniques, such as cellular-level connectomics image analysis and compressed sensing MRI reconstruction.