智慧感知與機器學習
Intelligent Sensing and Machine Learning
| 節 | 週一 |
|---|---|
3 10:10–11:00 | 智慧感知與機器學習 ED102 2 節連堂 |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
由於機器學習以及深度學習的相關技術不斷進步,許多影像處理方面的新技術不斷的被開發出來。除了影像及視覺之外,在應用面還有許多相關的感測器,也都能夠不斷地收集資料,形成所謂的巨量資料。這些感測器的資料,可以透過機器學習或是深度學習的技術加以分析,得到更豐富的高階資訊,同時感測器資料也可以和電腦視覺互相結合,進行感測資料融合。本課程將介紹相關智慧感知的深度學習技術: (i) 進行相關前沿論文(SOTA)的探討, (ii)學生透過探索相關主題之論文,整理成為論文(Learn to write Introduction, Related work, Problem statement, Method/Algorithm)
One of the followings: computer vision, machine learning, and deep learning (or related)
The course mainly contains a sequence of oral presentations of recent papers.
oral presentation: 50% technical writing: 50%
| 週次 | 主題 |
|---|---|
| 第 1 週 | recent papers in FL |
| 第 2 週 | recent papers in precision sports |
| 第 3 週 | recent papers in precision sports |
| 第 4 週 | recent papers in generative technology |
| 第 5 週 | recent papers in generative technology |
| 第 6 週 | medical imaging |
| 第 7 週 | dataset curation |
| 第 8 週 | video technology |
| 第 9 週 | video technology |
| 第 10 週 | |
| 第 11 週 | AI security |
| 第 12 週 | AI security |
| 第 13 週 | technical writing and discussion |
| 第 14 週 | technical writing and discussion |
| 第 15 週 | technical writing and discussion |
| 第 16 週 | final wrap-up |
recent papers in federated learning, recent papers in precision sports and posture research, recent papers in generated images/videos, recent papers in medical imaging, recent works in dataset curation, recent progresses in video technology, recent papers in AI security
- 地點
- EC room 533
- 時間
- Monday 12:00-13:00
- 聯絡方式
- Please check personal webpage (search "yctseng", and follow department webpage).