國立成功大學電機工程學系 教師個人頁面
English Version
蔡家齊 助理教授
地址
電機系館5樓92510室
Email
TEL
06-2757575 ext.62425
實驗室網站連結
AI System Lab 人工智慧系統實驗室
(R92529, 92526/ext.62400-1727)
學經歷
學歷
2020
國立交通大學電子所博士
2015
國立交通大學電子系學士
經歷
2021~present
國立成功大學電機工程學系助理教授
2020~2021
聯發科技資深工程師
2015~2020
聯發科技工程師
研究領域
  • AI 模型架構與壓縮(AI Model Architectrue and Compression)
  • AI 加速器(AI Accelerator)
  • AI 影像/聲音應用(AI-based Vision/Audio Application)
  • 機器學習(Machine Learning)
  • 嵌入式系統(Embedded System)
  • 電腦視覺(Computer Vision)
  • 數位訊號處理(Digital Signal Processing)
  • 軟硬體整合設計(SW/HW Co-design)
著作
期刊論文( Journal )
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  1. C. -C. Tsai and J. -I. Guo, "IVS-Caffe--Hardware-Oriented Neural Network Model Development," in IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2021.3072145. (IF=11.6)
  2. C.-C. Tsai, C.-Y. Lin, and J.-I. Guo, "Dark channel prior based video dehazing algorithm with sky preservation and its embedded system realization for ADAS applications," Optics express, vol. 27, no. 9, pp. 11877-11901, 2019. (IF=3.6)
  3. J.-I. Guo, C.-C. Tsai, J.-L. Zeng, S.-W. Peng, and E.-C. Chang, "Hybrid Fixed Point/Binary Deep Neural Network Design Methodology for Low Power Object Detection," in IEEE Journal on Emerging and Selected Topics in Circuits and Systems. (IF =3.4)
會議論文( Conference )
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  1. C.-C. Tsai, C.-K. Tseng, H.-C. Tang, and J.-I. Guo, "Vehicle detection and classification based on deep neural network for intelligent transportation applications," in 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2018: IEEE, pp. 1605-1608.
  2. C.-C. Tsai, Y.-T. Lai, Y.-F. Li, and J.-I. Guo, "A vision radar system for car safety driving applications," in 2017 International Symposium on VLSI Design, Automation and Test (VLSI-DAT), 2017: IEEE, pp. 1-4.
  3. C.-C. Tsai et al., "The 2020 Embedded Deep Learning Object Detection Model Compression Competition for Traffic in Asian Countries," in 2020 IEEE International Conference on Multimedia & Expo (ICME), 2020.
  4. J.-I. Guo, C.-C. Tsai et al., "Summary Embedded Deep Learning Object Detection Model Competition," in 2019 IEEE 21st International Workshop on Multimedia Signal Processing (MMSP), 2019: IEEE, pp. 1-5.
  5. C.-K. Tseng, C.-C. Tsai, and J.-I. Guo, "Pvalite CLN: Lightweight Object Detection with Classfication and Localization Network," in the 2019 32nd IEEE International System-on-Chip Conference (SOCC), Singapore, 2019.
  6. F.-A. Chang, C.-C. Tsai, C.-K. Tseng, and J.-I. Guo, "Embedded multiple object detection based on deep learning technique for advanced driver assistance system," in 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), 2017: IEEE, pp. 172-175.
  7. Y.-T. Lai, C.-C. Tsai, and J.-I. Guo, "Lane Departure Warning System Combining with Curve Lane Detection for Lane Keeping Applications," in the 2017 VLSI Design/CAD Symposium (VLSI-CAD), 2017.
  8. S.-M. Chang, C.-C. Tsai, and J.-I. Guo, "A Blind Spot Detection Warning System based on Gabor Filtering and Optical Flow for E-mirror Applications," in 2018 IEEE International Symposium on Circuits and Systems (ISCAS), 2018: IEEE, pp. 1-5.
  9. G.-T. Lin, P. S. Santoso, C.-T. Lin, C.-C. Tsai, and J.-I. Guo, "One Stage Detection Network with an Auxiliary Classifier for Real-Time Road Marks Detection," in 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2018: IEEE, pp. 1379-1382.
  10. T.-E. Wu, C.-C. Tsai, and J.-I. Guo, "LiDAR/camera sensor fusion technology for pedestrian detection," in 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2017: IEEE, pp. 1675-1678.
  11. Y.-F. Li, C.-C. Tsai, Y.-T. Lai, and J.-I. Guo, "A multiple-lane vehicle tracking method for forward collision warning system applications," in 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2017: IEEE, pp. 1061-1064.
專利
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其他
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研究計劃
  1. AI環境聲音偵測技術開發, 奇景光電
  2. 前瞻顯示科技與跨領域應用教學聯盟計畫, 教育部
  3. 智慧製造之多站點全流程優化, 科技部, 友達光電
  4. Project Executor, 以視覺應用為主之超低耗電穿戴式裝置晶片系統與軟體研究, 科技部
  5. Project Executor, 影像式內視鏡即時除霧技術開發, 科技部
  6. Project Executor, 多重感測訊號融合之障礙物辨識技術與系統實現, 科技部
  7. Project Executor, Auto-STR,從感知到反應:自動駕駛車應用之各式物件即時認知與駕駛反應技術及系統研發計畫-總計畫暨子計畫一:Auto-STR 應用之視覺深度學習物件行為辨識技術與駕駛反應技術, 科技部
  8. Project Executor, 結合深度學習與多重感測訊號融合之障礙物辨識技術, 科技部
  9. Project Executor, 應用於ADAS/特殊用途無人載具之嵌入式AI深度學習技術, 科技部
  10. Project Executor, 科管局研發精進計畫: 應用於智慧車載影像之光場影像記錄裝置與影像處理技術開發計畫, 中強光電
  11. Project Executor, 自動緊急剎車應用之物件偵測技術, 聯發科技
  12. Project Executor, BSD技術開發, 和碩聯合科技
  13. Project Executor, 深度學習之車輛偵測與車型辨識, 鐵雲科技
  14. Project Executor, 科管局研發精進計畫-大視角暨高動態光場取像裝置於物件辨識與偵測技術, 中強光電
  15. Project Executor, Field try experiments on ADAS Technology for Rear view obstacle detection/BSD/LDWS/FCWS/PD applications, 聯發科技
  16. Project Executor, 道路標線偵測模組委託開發, 工研院
  17. Project Executor, 行人偵測技術, 光寶科技
  18. Project Executor, 深度學習道路標線偵測模組, 工研院
  19. Project Executor, Key technology development/evaluation for autonomous driving applications, 聯發科技
  20. Project Executor, 打造工業物聯網WISE-PaaS教材設計, 研華
  21. Project Executor, 車流型態深度學習解析技術, 資策會
  22. Project Executor, Embedded Sensor Fusion Technology and Data Collection for ADAS/Self-driving Applications, 聯發科技
  23. Project Executor,Embedded camera/radar sensor fusion for object detection/tracking in 5G enabled applications, 鴻海精密
  24. Project Executor,Heterogeneous 9-ch camera/77GHz radar/lidar (32-bin) data collection and sensor fusion algorithm derivation for ADAS/Self-driving applications, Qualcomm
  25. Project Executor,Embedded camera/radar sensor fusion for object detection/tracking in 5G enabled applications, 鴻海精密
指導學生
本學年度 實驗室成員
博士班
郭原宏
王士逢
陳柏翰
羅祥睿
張峻豪
碩士班
高自在
李政憲
林明賜
吳振瑋
陳閔祥
洪翊珈
許奭民
蔡旻佑
盧正謀
黃瀞儀
黃姵瑄
湯詠涵
吳昀鴻
蔡承達
柯秉鈞
羅宇宸
游景翔
金稟鈞
許丞翔
林泳陞
許峻祐
曾柏硯
吳柄葳
郭君瑋
張茹涵
林芷萱
楊宗軒
林趺菩
已畢業學生
碩士班
111
王柏鈞   翁子浩   呂科進
特殊榮譽
  1. 2020年 參加第二十屆旺宏金矽獎半導體設計與應用大賽,"混合卷積神經網路硬體加速器系統設計與其模型訓練分析工具Hybrid CNN Accelerator System Design and the Associated Model Training/Analyzing Tools" 榮獲 評審團銀獎。
  2. 2017年 參加第十七屆旺宏金矽獎半導體設計與應用大賽,"Stand By You-基於深度學習之駕駛學習輔助系統Driving Learning Assistance System Based on Deep Learning" 榮獲 優勝獎。