人工智慧普適研究中心 PAIR Labs
人工智慧普適研究中心 PAIR Labs
機器人與感測技術領域
交通大學電機學院 郭峻因教授
計畫主持人(PI):郭峻因教授
AI計畫題目
核心技術
本計畫進行嵌入式AI深度學習技術開發,著重在ADAS/自駕車系統應用,從五大面向著手進行技術研發,包含自動化圖資標記與資料庫建置、深度學習軟硬體核心模型開發與加速器設計、各式 ADAS/自駕車應用感知深度學習技術、自駕車駕駛控制技術與系統模擬驗證環境等。
可應用領域
1. 先進駕駛輔助系統
2. 無人載具自駕車系統
3. 自駕輪椅
4. 工業用無人搬運車
5. 自動駕駛農用機械
現有可技轉技術
1. Embedded MTSAN model for deep learning object detection/segmentation in ADAS applications
2. Embedded camera/radar sensor fusion technology
3. ezLabel, a fast deep learning object labeling tool
4. ezQUANT, a bit-accurate deep learning model quantization/training tool for deep learning accelerators
5. ezHybrid-M, a hybrid fixed point/binary CNN model training tool for low-power object detection/classification applications
6. Modularized self-driving hardware/software systems for niche self-driving applications
開發中之技術
(可合作或未來技轉)
1. A vector-map free self-driving system based on Autoware
2. Embedded object detection/tracking for ADAS/Self-driving
3. Embedded instance/semantic segmentation
尋求產學合作的
新技術提案
1. Deep learning ADAS system
2. Self-driving hardware/software technology for niche market applications
3. Camera/radar sensor fusion system for smart transportation
4. Embedded AI deep learning technology development
5. Automatic labeling tool for object detection/behavior analysis in camera/radar/lidar domains
6. Hybrid fixed point/binary CNN hardware accelerator for edge AI applications
7. 360 video SLAM and camera/radar fusion SLAM for self-driving applications
8. Embedded moving object behavior analysis