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我是 孟倫

Meng-Luen "Frank" Wu

我的簡歷

基本介紹 Biography

姓名
Name
吳孟倫
Meng-Luen "Frank" Wu
最高學歷
Education
國立臺灣科技大學 資訊工程系 工學博士
Ph.D. in Computer Science, NTUST
次要學歷
Secondary
Education
國立臺北大學 法律學系財經法組 法學士
B.S. in Law, Financial Divison, NTPU
國立臺北大學 資訊工程學系 工學學士
B.S. in Computer Science, NTPU
專長
Expertise
人工智慧、資訊挖掘、智慧型法學系統、智慧財產權
Computer Vision, Artificial Intelligence, Intelligent Law Systems
興趣
Interest
創新創業、單眼攝影、汽機檔車
Entrepreneurship, DSLR, Automobile

吳孟倫於1987年出生於台北內湖。2006年畢業於台北市立內湖高中,2011年畢業於國立台北大學法律學系財經法組與資訊工程學系雙主修,2017年畢業於國立台灣科技大學資訊工程系博士班。吳孟倫的研究興趣在於影像處理、電腦視覺、資料探勘、深度學習、法學資訊系統等。研究方向在於以人工智慧為基底做跨領域的整合。

Meng-Luen Wu was born in 1987 in Neihu, Taipei. He graduated from Neihu Senior High School in Taipei City in 2006. He graduated from the Department of Law in Finance and Economics Division and the Department of Computer Science at the National Taipei University in 2011. He graduated from the National Taiwan University of Science and Technology in 2017 as a Ph.D. Wu's research interests include image processing, computer vision, data mining, deep learning, and intelligent law systems. His research direction is cross-discipline artificial intelligence systems, especially on legal affairs.



學歷 Education

國立臺灣科技大學資訊工程系工學博士
2013 - 2017
Ph.D. in Computer Science, NTUST, Taipei, Taiwan (R.O.C.)

專研人工智慧與影像處理、資料探勘與社群網路。Specializes in artificial intelligence and image processing, data mining and social networking.

國立臺灣科技大學資訊工程系碩士班
2011 - 2013
Master Program in Computer Science, NTUST, Taipei, Taiwan (R.O.C.)

專研影像處理、成像技術與設備。Specializes in image processing, imaging technology and equipment.

國立臺北大學資訊工程學系工學學士
2007 - 2011
B.S. in Computer Science, NTPU, New Taipei City, Taiwan (R.O.C.)

對於資料庫系統、影像處理、網路程式設計較為熟悉。Familiar with database system, image processing, and network programming.

國立臺北大學法律學系財經法組法學士
2006 - 2011
B.S. in Law (Financial and economic law division), NTPU, New Taipei City, Taiwan (R.O.C.)

對於智慧財產權、公司法、行政法較為熟悉。Familiar with copyright law, corporation law, and administration law.

主要經歷 Experience

淡江大學 資訊工程學系 助理教授
Assistant Professor in Computer Science, TKU

人工智慧、巨量資料、智慧型監控、法學系統。 Deep Learning, Image Processing, Data Mining, and Embedded Systems.

國立臺北大學 資訊工程學系 兼任助理教授
Adjunct Professor in Computer Science, NTPU

行動裝置應用程式開發 Development of Application Program for Mobile Device

國立臺灣科技大學資訊工程系博士後研究員
Postdoctoral Researcher in Computer Science, NTUST

深度學習、影像處理、資料探勘、嵌入式系統。 Deep Learning, Image Processing, Data Mining, and Embedded Systems.

國立臺灣師範大學電機工程學系兼任研究助理
Adjunct Research Assistant in Electrical Engineering, NTNU

眼動儀裝置軟體開發 Eye Tracking Software Development

資訊工業策進會兼任研究人力
Adjunct Research Assistant, Institute for Information Industry

物聯網與智慧微導購研究 Internet of Things and Smart Shopping Guiding Systems Research

中央研究院資訊科學研究所研究助理
Adjunct Research Assistant in Computer Science, Academia Sinica

社群網路與網路爬蟲 Social Network and Internet Crawler

榮譽獎項 Honor

  • 2016 科技部 創新創業激勵計畫第二梯次入圍 (隊長/線上法律諮詢系統)
  • 2014 國立臺灣科技大學新事業發展競賽入圍決賽 (隊長/影片濃縮系統)
  • 2014 科技部 創新創業激勵計畫第一梯次入圍 (隊長/影片濃縮系統)
斐陶斐榮譽會員
2014 台灣科技大學電資學院傑出青年
2012 教育部全國微電腦競賽第二名
2010 國立臺北大學 資訊工程學系期末專題競賽第二名
2013 經濟部技術處搶鮮大賽優秀獎
2012 經濟部工業局通訊大賽優等獎
2010 美商華麗得 Wattleader 創意程式競賽 創新獎
2009 經濟部工業局通訊大賽最佳校園創意獎

著作 Publications

期刊論文 Journal Papers

  1. C. S. Fahn, C. Y. Kao, M. L. Wu, and H. E. Chueh, "SOINN-Based Abnormal Trajectory Detection for Efficient Video Condensation", Computer Systems Science and Engineering, vol. 42, no. 2, pp. 451-463, 2022. doi:10.32604/csse.2022.022368 (included in SCI)
  2. B. S. Lin, I. J. Lee, C. S. Fahn, Y. F. Lee, W. J. Chou, and M. L. Wu "Depth-Camera Based Energy Expenditure Estimation System for Physical Activity Using Posture Classification Algorithm," Sensors, vol. 21, no. 12, pp. 4216, June 2021. doi:10.3390/s21124216 (included in SCI & EI)
  3. Y. S. Chen, S. W. Chiang, and M. L. Wu, "A Few-Shot Transfer Learning Approach Using Text-label Embedding with Legal Attributes for Law Article Prediction," Applied Intelligence, May 2021. doi:10.1007/s10489-021-02516-x (included in SCI & EI)
  4. C. S. Fahn, G. Ling, M. Y. Yeh, P. Y. Huang, and M. L. Wu, “Abnormal Maritime Activity Detection in Satellite Image Sequences Using Trajectory Features,” International Journal of Future Computer and Communication, vol. 8, no. 1, pp. 29-33, 2019. doi:10.18178/ijfcc.2019.8.1.535 (included in EI)
  5. C. S. Fahn, and S. E. Lee, and M. L. Wu “Real-Time Musical Conducting Gesture Recognition Based on a Dynamic Time Warping Classifier Using a Single-Depth Camera,” Applied Sciences, vol. 9, no. 3, pp. 528-538, Feb. 2019. doi: 10.3390/app9030528 (included in SCI)
  6. M. L. Wu, C. S. Fahn, and Y. F. Chen, “Image-format-independent Tampered Image Detection Based on Overlapping Concurrent Directional Patterns and Neural Networks.” Applied Intelligence, pp. 1-15, Mar. 2017. doi: 10.1007/s10489-017- 0893-4 (included in SCI & EI)
  7. C. S. Fahn, C. Y. Kao, C. B. Yao, and M. L. Wu, “Exploiting AdaRank Model and Trajectory of Hand Motion for Hand Gesture Recognition,” Sensor Letters, vol. 14, no. 10, pp. 1061-1065, Oct. 2016. doi: 10.1166/sl.2016.3743 (included in SCI & EI)

研討會論文 Conference Papers

  1. M. L. Wu, G. Lin, and P. C. Yu, "On the development of a legal penalty prediction system for drunk driving cases," in Proceedings of the International Conference on Machine Learning and Cybernetics, Toyama, Japan, 2022.
  2. C. S. Fahn, M. L. Wu, and S. K. Tsau, "An intelligent photographing guiding system based on compositional deep features and intepretable machine learning model," in Proceedings of the International Conference on Pattern Recognition, Milan, Italy, 2021.
  3. C. S. Fahn, Y. L. Wang, C. P. Lee, and M. L. Wu, "A novel Chinese reading comprehension model based on attention mechanism and convolutional neural networks," in Proceedings of the International Conference on Machine Learning and Cybernetics, Adelaide, Australia, 2020.
  4. C. S. Fahn, T. Y. Wu, and M. L. Wu, "A Cross-Dataset Evaluation of Anti-Face-Spoofing Methods Using Random Forest and Convolutional Neural Network," in Proceedings of the International Conference on Asian Digital Image Processing, Kobe, Japan, 2019.
  5. C. S. Fahn, J. Ling, M. Y. Yeh, and M. L. Wu, "A Real-Time Cloud Detection System Using an End-to-End Multiscale Deep Learning Approach," in Proceedings of the International Conference on Astronautics and Space Exploration, Hsinchu, Taiwan, 2019.
  6. C. S. Fahn, J. Ling, M. Y. Yeh, M. L. Wu, Y .C. Lan, W. Y. Chao, H. C. Wu, Y. C. Huang, and T. Y. Lu, "A novel cloud detection and satellite attitude planning method for captuing cloudless remote sensing images," in Proceedings of the International Conference on Artificial Intelligence and Soft Computing, Bangkok, Thailand, 2019.
  7. C. S. Fahn, J. Ling, M. Y. Yeh, and M. L. Wu, "A Novel Cloud Detection and Satellite Attitude Planning Method for Capturing Cloudless Remote Sensing Images," in Proceedings of the Astronautical Exploration Technology Workshop, Hsinchu, Taiwan, 2019.
  8. Y. S. Chen, H. C. Chi, M. L. Wu, and E. C. Sung, “A Machine Learning Based Prediction System of Medical Laws Judgment Using Statute-Classified Decision Tree with Text Similarity,” in Proceedings of TANET 2018, Taoyuan, Taiwan, Oct. 2018, pp. 1253-1258. doi: 10.1109/TENCON.2018.8650544 (Best Paper Award)
  9. C. S. Fahn, C. Y. Pan, and M. L. Wu, “An Aesthetic Preference Prediction System for Assessing Natural Images Based on Photo Complexity and Composition Evaluation,” in Proceedings of IEEE Region 10 Conference, Jeju, South Korea, Oct. 2018, pp. 634-639. doi: 10.1109/TENCON.2018.8650544
  10. M. L. Wu and C. S. Fahn, “A Real-time Professional Photographing Guiding System through Image Composition Analysis,” in Proceedings of International Conference on Human-Computer Interaction, Vancouver, Canada, Jul. 2017, pp. 466-477. doi: 10.1007/978-3-319-57987-0_38
  11. C. S. Fahn, M. L. Wu, and C. C. Liu, “A Surveillance Video Condensation System Based on the Spatial and Temporal Rearrangement of Moving Object Trajectories,” in Proceedings of International Workshop on Advanced Image Technology, Penang, Malaysia, Jan. 2017.
  12. M. L. Wu and C. S. Fahn, “A Decision Tree Based Image Enhancement Instruction System for Producing Contemporary Style Images,” in Proceedings of International Conference on Human-Computer Interaction, Toronto, Canada, Jul. 2016, pp. 80-90, doi: 10.1007/978-3-319-40349-6_9
  13. H. F. Ho, M. L. Wu, P. Y. Hsiao, and G. A. Chen, “Feasibility of an Asymmetric Hyperboloid Mirror for Surveillance Systems,” in Proceedings of International Conference on Digital Signal Processing, Singapore, Singapore, Jul. 2015, pp. 868-872. doi: 10.1109/ICDSP.2015.7252000
  14. C. S. Fahn, B. Y. Su, and M. L. Wu, “Vision-based Identification Extraction for Freight Containers,” in Proceedings of International Conference on Wavelet Analysis and Pattern Recognition, Guangzhou, China, Jul. 2015, pp. 51-57. doi: 10.1109/ICWAPR.2015.7295925
  15. C. S. Fahn, B. Y. Su, and M. L. Wu, “A Virtual Handwriting Tablet Based on Pen Shadow Cues,” in Proceedings of International Conference on Human-Computer Interaction, Crete, Greece, Jun. 2014, pp. 224-233. doi: 10.1007/978-3-319-07230-2_22
  16. C. S. Fahn and M. L. Wu, “An Autonomous Aesthetics-driven Photographing Instructor with Personality Prediction,” in Proceedings of International Conferences on Computer Graphics, Visualization, Computer Vision, and Game Technology, Jakarta, Indonesia, Dec. 2013, pp. 13-19. doi:10.2991/visio-13.2014.3
  17. C. S. Fahn, M. L. Wu, and W. T. Liu, “On the Use of Augmented Reality Technology for Creating Interactive Computer Games,” in Proceedings of Virtual, Augmented and Mixed Reality. Systems and Applications, Las Vegas, Nevada, Jul. 2013, pp. 353-362. doi:10.1007/978-3-642-39420-1_37

專書論文 Book Chapters

  • C. S. Fahn and M. L. Wu, “On the Design of a Photo Beauty Measurement Mechanism,” in Perception of Beauty, M. P. Levine, Ed. Rijeka, Croatia: IntechOpen, 2017. doi:10.5772/intechopen.69502

專利 Patents

  1. C. S. Fahn and M. L. Wu, “自動尋景拍攝方法及其系統,” R.O.C. Patent I532361, May 1, 2016.
  2. C. S. Fahn, M. L. Wu, and C. C. Liu, “一種影片濃縮之系統及方法,” R.O.C. Patent I511058, December 1, 2015.
  3. C. S. Fahn and M. L. Wu, “Automatic photographing method and system thereof,” U. S. Patent 9 106 838, August 11, 2015.

科技部計畫 Project

  1. 2022 基於深度學習的照片美學評估與攝影指引(MOST 111-2221-E-032-020-) 主持人
  2. 2021 基於人工智慧的法律科技技術研發–法學資料檢索與案件結果預測(MOST 110-2222-E-032-004-) 主持人
  3. 2020 基於人工智慧之刑法量刑預測技術和系統(MOST 109-2221-E-305-014-) 共同主持人

可開授課程 Lectures

計算機概論

Introduction to
Computer Science

資料庫系統

Database
Systems

人工智慧

Artificial
Intelligence

計算機程式設計

Computer
Programming

物件導向程式設計

Object-oriented
Programming

APP 程式開發

Mobile Device
Programming

會員 Membership

  1. IEEE Computer Society Membership Taipei Section
  2. 中華民國影像處理暨圖形識別協會正會員
  3. 國立台灣科技大學第八屆院傑出青年
  4. 中華民國人工智慧學會會員
  5. 中華民國斐陶斐榮譽學會榮譽會員 2014

研究領域

智慧型影像審美與構圖分析

將影像構圖的數個關鍵特徵取出來,包含關鍵線條、視覺顯著區域、對焦清晰區域分析,並針對影像各個尺度做高斯金字塔,透過監督式學習,產生出構圖分類器。

衛星影像分析

智慧法學

沒有人想要當恐龍法官,但是法律上需要考量的因素太多,而在社會上的案量每天都在迅速累積,如何借助電腦的力量,幫助司法人員快速釐清案情,並提示法務人員應該注意的事項,是一門越來越重要的學問了。

作品

人工智慧 Artificial Intelligence

智慧型監控 Intelligent Surveillance

法學資訊系統 Intelligent Law System

APP設計 APP Development

遊戲設計 Game Development

興趣分享

單眼攝影

單眼攝影不只是操作機械,更是一種修身養性。單眼攝影是一種人與光線之間的溝通,若取景參數調整的好,能夠拍出手機相機拍不出的夢幻效果。
單眼相機,若是調成手動模式,光圈快門都要依賴自己判斷,需要熟練才能知道如何對應不同場景,參數該如何調整,鏡頭該如何選擇。夢幻的照片往往出於意外的參數調整,或是在嘗試新的取景方式後獲得的。更甚者,要在別人意想不到的時間,到別人不敢去的地方,也容易收穫滿滿。

創新創業

要真正做大事,光靠一個人是不夠的,現代像樣的事情得靠多人群策群力才能達成。透過創業,才知道公司管理大小事務多麼繁雜,小從人事,大至方向,以及財務,無不令人傷透腦筋。若只是創業而不創新,則只需要管理不需點子。而創新是一種冒險,嘗試別人沒有做過的事,巨大的收穫往往來自巨大的冒險。

機械鐘錶

機械鐘完全不倚賴電力,是一個完全使用發條作和地心引力來作動的裝置,它的時間準確完全由鐘擺的配重決定。配重過多,則時間走得慢;配重過輕,則時間走得太快。有些時鐘在發條剛轉緊時,也會走得比較快,而隨著發條越來越鬆,走的越來越慢。今日的機械鐘由於準確度不如電子及石英鐘,修身養性的用途,已經超過了它的實用本身。