郭峻因教授

國立陽明交通大學電子研究所特聘教授

最高學歷：國立交通大學電子研究所博士
研究領域：VLSI, IP/SOC, Intelligent Vision System, Embedded Deep Learning Technology, ADAS/Autonomous Driving System

專業經歷：

• 國立交通大學電子工程學系特聘教授 (2017/6~)
• 國立陽明交通大學電機學院副院長 (2017/2~2022/08)
• 峻魁智慧股份有限公司創辦人 (2022/05~)
• 科技部半導體射月計畫主軸召集人 (2018/05-2022/06)
• 國立交通大學晶片系統研究中心主任 (2016/8~2019/7)
• 國立交通大學電子研究所所長 (2012/8~2015/7)
• 智慧電子國家型計畫分項召集人 (2011/1~2015/12)

傑出成就：

• 科技部109年度傑出技術移轉貢獻獎
• 2020 第二十屆旺宏金矽獎設計組最佳指導教授獎
• 2019 科技部 AI 創新研究專案國際研討會暨聯合成果展最佳投資團隊獎第一名
• 2018 科技部未來科技展未來科技突破獎
• 科技部106年度傑出技術移轉貢獻獎
• 科技部105年度產學小聯盟之績優聯盟
• 105年科技部傑出研究獎
• 103年中國工程師學會傑出工程教授獎
• 101年國家發明獎銀牌
• 九十九年中國電機工程學會傑出工程教授獎
• 九十七年中國電機工程學會中區傑出工程教授獎

近期論文：

[1]	Hung-Wei Lin, Vinay M. Shivanna, Hsiu Chi Chang, and Jiun-In Guo,” Real-Time Multiple Pedestrian Tracking with Joint Detection and Embedding Deep Learning Model for Embedded Systems,” accepted by IEEE Access, April 9th, 2022. (SCI, IF=4.48, H-index=127, JCI Rank=58/223 in Engineering, Electrical and Electronics)
[2]	Tzu-Hsien Sang, Kuan-Yu Tseng, Feng-Tsun Chien, Chia-Chih Chang, Yi-Hsin Peng, and Jiun-In Guo, “Deep Learning-based Velocity Estimation for FMCW Radar with Random Pulse Position Modulation,” accepted by IEEE Sensors Letters, March 1st, 2022 (SCI, IF=2.36)
[3]	Yu-Shu Ni, Vinay Malligere Shivanna, Jiun-In Guo,” iVS Dataset and ezLabel: A Dataset and a Data Annotation Tool for Deep Learning based ADAS Applications,” Remote Sensing, 2022, 14, 833. (SCI, IF=4.848), https://doi.org/10.3390/rs14040833
[4]	Chia-Chi Tsai and Jiun-In Guo,” IVS-Caffe – Hardware-Oriented Neural Network Model Development,” IEEE Transactions on Neural Networks and Learning Systems (Early access), pp. 1-15, July 26th, 2021. (SCI, IF=12.51)
[5]	Chun-Yu Lai, Bo-Xun Wu, Vinay M. Shivanna, and Jiun-In Guo,” MTSAN: Multi-Task Semantic Attention Network for ADAS Applications,” IEEE Access, vol. 9, pp. 50700-50714, 2021. (SCI, IF=4.48)
[6]	Zohauddin Ahmad, Yan-Min Liao, Sheng-I Kuo, You-Chia Chang, Rui-Lin Chao, Naseem, Yi-Shan Lee, Yung-Jr Hung, Huang-Ming Chen, Jyehong Chen, Jiun-In Guo, and Jin-Wei Shi, “High-Power and High-Responsivity Avalanche Photodiodes for Self-Heterodyne FMCW Lidar System Applications,” IEEE Access, vol. 9, pp. 85661-85671, 2021. (SCI, IF=4.48)
[7]	Tzu-Hsien Sang, Feng-Tsun Chien, Chia-Chih Chang, Kuan-Yu Tseng, Bo-Sheng Wang, and Jiun-In Guo,” DoA Estimation for FMCW Radar by 3D-CNN,” Sensors, vol. 21, no. 16, Aug. 2021, (SCI, IF=3.576)
[8]	Yu-Ting Li, Paul Kuo and Jiun In Guo, “Automatic Industry PCB Board DIP Process Defect Detection System based on Deep Ensemble Self-Adaption Method,” IEEE Transactions on Components, Packaging and Manufacturing Technology, vol. 11, issue 2, pp. 312-323, Feb. 2021. (SCI, IF=2.31)
[9]	Wen-Chia Tsai, Jhih-Sheng Lai, Kuan-Chou Chen, Vinay M. Shivanna and Jiun-In Guo, “A Lightweight Motional Objects Behavior Prediction System Harnessing Deep Learning Technology for Embedded ADAS Applications,” Electronics, Electrical and Autonomous Vehicles session, special issue Autonomous Vehicles Technology, vol. 10, issue 6, pp. 692, 2021. (SCIE, IF=2.412)
[10]	Jiun-In Guo, Chia-Chi Tsai, Jian-Lin Zeng, Shao-Wei Peng, and En-Chih Chang,” Hybrid Fixed Point/Binary Deep Neural Network Design Methodology for Low Power Object Detection,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), vol. 10, no. 3. pp. 388-400, September 2020. (SCI, IF=4.643)
[11]	Guan-Ting Lin, Vinay Malligere Shivanna, and Jiun-In Guo, “A Deep Learning Model with Task-Specific Bounding Box Regressors and Conditional Back-Propagation for Moving Object Detection in ADAS Applications,” Sensors, special issue on “Sensor and Communication Systems Enabling Autonomous Vehicles”, vol. 20, no. 18, pp. 1-21, Sept. 2nd, 2020. (SCIE, IF=3.275)
[12]	Jin-Wei Shi, Jiun-In Guo, Manabu Kagami, Paul Suni, and Olaf Ziemann, “Photonic technologies for autonomous cars: feature introduction,” Optics Express, vol. 27, no. 5, pp. 7627-7628, March, 2019. (SCI, IF=3.356, ranked 1st out of 94 journals)
[13]	Chia-Chi Tsai, Cheng-Yen Lin, and Jiun-In 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, April 2019. (SCI, IF=3.356, ranked 1st out of 94 journals)
[14]	Vinay M. Shivanna, Kuan-Chou Chen, Bo-Xun Wu, and Jiun-In Guo,” A Comparison of Traditional and CNN Based Computer Vision Sensors for Detection and Recognition of Road Signs,” the Open Access book, “Vision Sensors” edited by Dr. Francisco J. Gallegos-Funes, July 13, 2021. (SCI) @ IntechOpen Book Chapter.