深度學習於智慧汽車應用
Deep Learning for Autonomous Driving
| 節 | 週一 | 週三 |
|---|---|---|
5 13:20–14:10 | 深度學習於智慧汽車應用 ED103 | |
7 15:30–16:20 | 深度學習於智慧汽車應用 ED103 2 節連堂 | |
8 16:30–17:20 |
* 根據陽明交大上課時間表所列
課程目標:本課程模組目標為學生可自行開發以深度學習方法應用於智慧汽車系統,可訓練學生對於深度學習及智慧車的概念,在未來進一步實際運用於自走車及智慧交通系統等進階教學、實驗課程模組。 課程特色: PBL教學案例: 場景辨識與方向控制,目標95%正確率與30fps即時處理。 課程內容: □機器學習概論 □電腦視覺概論 □Convolutional neural network □Deep learning practices □Recurrent neural network □Object detection: 車輛與行人偵測/交通號誌偵測 □Motion planning: 車輛自動行進控制/ Reverse Reinforcement learning for driving learning 實習課程配合上述授課內容進行實際操作演練;期末專題則根據以上授課與實習內容,分小組進行設計與訓練測試,鼓勵學生以創意方式達成之課程目的。
probability linear algebra
all materials will be at NYCU e3 site 線上課程 (Microsoft teams) https://teams.microsoft.com/l/meetup-join/19%3aAW14taWzKp3vZB_LzKnopcrJrfCGg5lMM8bheoU3QvA1%40thread.tacv2/1631235553428?context=%7b%22Tid%22%3a%22010281b3-d5d6-4bc8-b561-bf4794b97036%22%2c%22Oid%22%3a%22e151df1b-24d2-4839-89ab-ea5b56386456%22%7d 團隊連結 (Use this to join teams without permission) https://teams.microsoft.com/l/team/19%3aAW14taWzKp3vZB_LzKnopcrJrfCGg5lMM8bheoU3QvA1%40thread.tacv2/conversations?groupId=61a23d52-b218-4970-8d4e-b02246e5a604&tenantId=010281b3-d5d6-4bc8-b561-bf4794b97036
Lab x5 (60%) Final project (20%) (2 persons in a group. topic survey + implementation) Final exam (20%)
| 週次 | 主題 |
|---|---|
| 第 1 週 | course introduction autonomous driving overview of computer vision: image classification |
| 第 2 週 | 中秋節 (9/20) neural network: introduction and back propagation 1st lab |
| 第 3 週 | Introduction of convolutional neural network |
| 第 4 週 | neural network training part 1 2nd lab |
| 第 5 週 | 10/11 (National holiday) advanced CNN architecture |
| 第 6 週 | neural network training part 2 3rd lab |
| 第 7 週 | semantic segmentation |
| 第 8 週 | Object detection 4th lab |
| 第 9 週 | Object detection |
| 第 10 週 | model simplification and acceleration |
| 第 11 週 | model simplification and acceleration 5th lab |
| 第 12 週 | Motion planning: 車輛自動行進控制/ Reverse Reinforcement learning for driving learning |
| 第 13 週 | Final Exam |
| 第 14 週 | recurrent neural network |
| 第 15 週 | Generative adversarial network and self driving |
| 第 16 週 | Generative adversarial network and self driving |
| 第 17 週 | 期末專題 |
| 第 18 週 | 期末專題 |
Course slides and papers will be our major source. reference: Deep Learning, Ian Goodfellow, Yoshua Bengio and Aaron Courville
- 地點
- ED406
- 時間
- W56, please make an appointment in advance.
- 聯絡方式
- e-mail: tschang@nycu.edu.tw TEL: 03-5731925 (NYCU local extension number: 31925)