Huimin Lu

luhuimin
Huimin Lu
Assistant Professor (Kyutech), Excellent Young Researcher (MEXT,Japan)
Kyushu Institute of Technology, Japan
ADD: E3-209, Sensui-cho 1-1, Tobata-ku, Kitakyushu 804-8550, Japan
TEL: +81-93-884-3183 FAX: +81-93-861-1159
Email: dr.huimin.lu*ieee.org (Please replace*with @)

GoogleScholar ORCID Publons SPIE Researchmap DBLP Scopus ResearchGate Kyutech

Huimin Lu received double M.S. degrees in Electrical Engineering from Kyushu Institute of Technology and Yangzhou University in 2011, respectively. He received a Ph.D. degree in Electrical Engineering from Kyushu Institute of Technology in 2014. From 2013 to 2016, he was a JSPS research fellow (DC2, PD, and FPD) at Kyushu Institute of Technology. Currently, he is an assistant professor in Kyushu Institute of Technology and an Excellent Young Researcher of Ministry of Education, Culture, Sports, Science and Technology-Japan. He serves as editor or associate editor for IEEE Access Journal, Computers & Electrical Engineering, Wireless Networks, etc. He is the Leading Guest Editor for ACM/Springer Mobile Networks and Applications, Optics & Laser Technology, Multimedia Tools and Applications, Applied Soft Computing, etc. His research interests include artificial intelligence, machine vision, deep-sea observing, internet of things and robotics. He has authored or co-authored 100+ papers in peer-reviewed journals and conferences, which have received 2000+ citations, 5 ESI highly cited papers and 5 ESI hot papers. As the lead editor, he has edited 3 books and have 75K+ downloads. He has received 20+ awards and 20+ funds from the governments and associations. He is elected as the Fellow of European Alliance for Innovation (EAI) in 2019.

Journal Editorial Board

Associate Editor, Applied Soft Computing-Elsevier
Associate Editor, Computers and Electrical Engineering-Elsevier
Associate Editor, IEEE Access Journal-IEEE
Associate Editor, Wireless Networks-Springer

Journal Reviewer

IEEE PAMI/TIP/TCSVT/TMM/CEM/Wireless Comm./Comm. Mag./Sensors Journal, PR, PRL, FGCS, ASOC, Information Fusion, etc.

Invited Talk

IEEE ERK2017; ISAIR2017;ISAIR2018;海中海底工学フォーラム・ZERO2019;

Conference Organizer

General Co-Chair: ISAIR2016; ISAIR2017; ISAIR2018;
Program Chair: ISAIR2019;
General Chair: EAI/ROSENET2017; EAI/ROSENET2018;EAI/ROSENET2019;
Workshop Chair: IEEE/ICPADS2016; EAI/TRIDENTCOM2017; ACPR2017; ACM/ICIMCS2018
Program Committee: PDCAT2019; ACPR2019;

Selected Journal Papers

  1. Y. Li, Y. Jiang, D. Tian, L. Hu, H. Lu, Z. Yuan, “AI-enabled emotion communication” IEEE Network, In Press, 2020.
  2. H. Lu, G. Liu, Y. Li, H. Kim, S. Serikawa, “Cognitive Internet of vehicles for automatic driving”, IEEE Network, vol.33, no.3, pp.65-73, 2019.
  3. X. Xu, H. Lu, J. Song, Y. Yang, H.T. Shen, X. Li, “Ternary adversarial networks with self-supervision for zero-shot cross-modal retrieval”, IEEE Transactions on Cybernetics, 2019.
  4. H. Lu, D. Wang, Y. Li, J. Li, X. Li, H. Kim, S. Serikawa, I. Humar, “CONet: A cognitive ocean network”, IEEE Wireless Communications, vol.26, no.3, pp.1-10, 2019.
  5. Y. Sakai, H. Lu, J. Tan, H. Kim, “Recognition of surrounding environment from electric wheelchair vedeos based on modified YOLOv2”, Future Generation Computer Systems, vol.92, pp.157-161, 2019.
  6. H. Lu, T. Uemura, D. Wang, J. Zhu, Z. Huang, H. Kim, “Deep-sea organisms tracking using dehazing and deep learning”, Mobile Networks and Applications, In Press, 2019.
  7. H. Lu, Y. Li, T. Uemura, H. Kim, S. Serikawa, “Low illumination underwater light field images reconstruction using deep convolutional neural networks”, Future Generation Computer Systems, vol.82, pp.142-148, 2018.
  8. Y. Zhang, R. Gravina, H. Lu, M. Villari, G. Fortino, “PEA: Parallel electrocardiogram-based authentication for smart healthcare systems”, Journal of Network and Computer Applications, vol.117, pp.10-16, 2018.
  9. W. Zhao, H. Lu, D. Wang, “Multisensor image fusion and enhancement in spectral total variation domain”, IEEE Transactions on Multimedia, vol.20, no.4, pp.866-879, 2018.
  10. H. Lu, Y. Li, S. Mu, D. Wang, H. Kim, S. Serikawa, “Motor anomaly detection for unmanned aerial vehicles using reinforcement learning”, IEEE Internet of Things Journal, vol.5, no.4, pp.2315-2322, 2018.
  11. Y. Li, H. Lu, K. Li, H. Kim, S. Serikawa, “Non-uniform de-scattering and de-blurring of underwater images”, Mobile Networks and Applications, vol.23, pp.352-362, 2018.
  12. H. Lu, Y. Li, M. Chen, H. Kim, S. Serikawa, “Brain Intelligence: go beyond artificial intelligence”, Mobile Networks and Applications, vol.23, pp.368-375, 2018.
  13. H. Lu, B. Li, J. Zhu, Y. Li, Y. Li, L. He, J. Li, S. Serikawa, “Wound intensity correction and segmentation with convolutional neural networks,” Concurrency and Computation: Practice and Experience, vol.29, no.6, pp.3927, 2017.
  14. Y. Li, H. Lu, J. Li, X. Li, Y. Li, S. Serikawa, “Underwater image de-scattering and classification by deep neural network”, Computers and Electrical Engineering, vol.54, pp.68-77, 2016.
  15. H. Lu, Y. Li, S. Nakashima, S. Serikawa, “Turbidity underwater image restoration using spectral properties and light compensation”, IEICE Transactions on Information and Systems, vol.E-99D, no.1, pp.219-227, 2016.
  16. H. Lu, Y. Li, S. Nakashima, S. Serikawa, “Single image dehazing through improved atmospheric light estimation”, Multimedia Tools and Applications, vol.75, no.24, pp.17081-17096, 2016.
  17. H. Lu, Y. Li, L. Zhang, S. Serikawa, “Contrast enhancement for images in turbid water”, Journal of Optical Society of America-A, vol.32, no.5, pp.886-893, 2015.
  18. S. Serikawa, H. Lu, “Underwater image dehazing using joint trilateral filter”, Computers and Electrical Engineering , vol.40, no.1, pp.41-50, 2014.
  19. H. Lu, Seiichi Serikawa, “Design of freely configurable safety light curtain using hemispherical mirrors”, IEEJ Transactions on Electrical and Electronic Engineering, vol.8, no.S1, pp.S110-S111, 2013.
  20. H. Lu, L. Zhang, S. Serikawa, “Maximum local energy: an effective approach for image fusion in beyond wavelet transform domain”, Computers & Mathematics with Applications, vol.64, no.5, pp.996-1003, 2012.

Selected Conference Papers

  1. Z. Wang, Z. Huang, Y. Luo, H. Lu, “Object interaction-aware visual dialogue generation”, ACMMM2019.
  2. X. Xu, J. Song, H. Lu, Y. Yang, F. Shen, Z. Huang, “Modal-adversarial Semantic Learning Network for Extendable Cross-modal Retrieval”, Proc. of 2018 ACM on International Conference on Multimedia Retrieval (ICMR2018), pp.46-54, 2018.
  3. X. Xu, J. Song, H. Lu, L. He, Y. Yang, F. Shen, “Dual Learning for Visual Question Generation”, Proc. of 2018 IEEE International Conference on Multimedia and Expo (ICME2018), pp.1-6, 2018.
  4. L. He, X. Xu, H. Lu, Y. Yang, F. Shen, H. Shen, “Unsupervised cross-model retrieval through adversarial learning”, Proc. of 2017 IEEE International Conference on Multimedia and Expo (ICME2017), pp.1-6, 2017.
  5. H. Lu, Y. Li, X. Xu, L. He, D.G. Dansereau, S. Serikawa, “Underwater image descattering and quality assessment”, Proc. of 2016 IEEE International Conference on Image Processing (ICIP2016), pp.1998-2002, 2016.
  6. H. Lu, Y. Li, S. Serikawa, J. Li, Z. Liu, X. Li, “Image restoration method for deep-sea tripod observation systems in the South China Sea”, Proc. of MTS/IEEE Oceans 2015, pp.1-6, Washington DC, USA.
  7. H. Lu, Y. Li, S. Serikawa, “Single underwater image descattering and color correction”, Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2015), pp.1623-1627, 2015.
  8. H. Lu, S. Serikawa, “Underwater scene enhancement using weighted guided median filter”, Proc. of IEEE International Conference on Multimedia and Expo (ICME2014), pp.1-6, 2014.
  9. H. Lu, Y. Li, S. Serikawa, “Underwater image enhancement using guided trigonometric bilateral filter and fast automatic color correction”, Proc. of 2013 IEEE International Conference on Image Processing (ICIP2013), pp.3412-3416, 2013.
  10. H. Lu, Y. Li, L. Zhang, A. Yamawaki, S. Yang, S. Serikawa, “Underwater optical image dehazing using guided trigonometric bilateral filtering”, Proc. of 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), pp.2147-2150, 2013.

Books

  1. Artificial Intelligence and Computer Vision (Springer-Nature, 2017) http://www.springer.com/us/book/9783319462448 (14K+ downloads)
  2. Artificial Intelligence and Robotics (Springer-Nature, 2018) http://www.springer.com/la/book/9783319698762 (60K+ downloads/Top 10 Downloaded Books of Springer in 2018)
  3. Cognitive Internet of Things: Frameworks, Tools and Applications (Springer-Nature, 2019) https://www.springer.com/jp/book/9783030049454

陆慧敏(工学博士)

九州工业大学助理教授・日本文部科学省卓越研究员
地址:日本国福冈县北九州市户畑区仙水町1-1E3-209室,邮编 804-8550
电子邮件:dr.huimin.luieee.org (请将邮箱地址中的*置换为@)
陆慧敏博士,20116获得扬州大学和九州工业大学工学双硕士学位(获江苏省优秀硕士学位论文、IEEE冈支部优秀学生研究奖)20143月提前获得九州工业大学电气电子工学系工学博士学位(2012年中国国家优秀自费留学生奖)20134月至20169月任日本学术振兴会特别研究员(历任DC2PDFPD)20169月入选日本文部科学省第一批青年千人计划卓越研究员事业201610月起任九州工业大学工学研究院机械知能工学系助教。2017年起主持九州工业大学智能共融机器人重点研发计划,积极推广人工智能和智能物联网在产业机器人领域的研究与应用。2018年起参与日本政府地方大学・企业发展改革事业(基于先进机器人技术的企业高度自动化产业改革项目),联合安川电机、卢布雅尔那大学等多家单位联合推进智能机器人产业的国际化工作。

研究方向

课题1)深海资源探测与开发技术研究开发
21纪人类进入了开发和利用海洋的新时代,海洋科技已进入全球科技竞争的前沿,并成为国际综合实力较量的焦点之一。发展海洋科技,尤其是深海高新技术已成为世界新技术革命的重要内容,海洋科技进步已经成为衡量国家科技总体水平和海洋强国的重要指标之一。自1970年起,世界各国开始不断对深海渔业资源和矿产资源进行探测。到目前为止,在4000米以下区域不断发现了新的生物物种、甲烷水合物、锰结核、钴结核、热水矿床等。日本、美国、俄罗斯、法国、英国、德国等几个海洋先进国已经拥有6000米以上深度探测的深海探查机,这些装备到达的范围遍及海洋的大陆坡、海山顶、火山口、洋脊以及6000米以下的洋底,在地质、地球化学、地球物理和海洋生物等方面取得了大量的重要发现。由此可见,近年来,世界强国对海洋的开发、研究和控制的特点已初现端倪,其中的重头戏就是向深海进军。但是,目前深海探测仍然存在许多问题。本研究将着眼于研究设计先进的水下机械电子设备,为传统的水下作业系统提供高精度的探测设备,为深海资源探测与资源开发提供可靠的技术保障。

课题2)下一代人工智能及其在机器人领域的应用
人类社会进入21纪以来,智能机器人开发逐渐得到各国的高度重视。智能机器人集成应用了计算机与网络技术,物联网技术、机械控制技术和遥感测绘技术。从2013年起、大数据科学的突猛发展促进了当今机器人革新。小型化便携式机器人会取代传统的机械式机器人,将成为未来机器人发展的主要方向之一。近年,通过对各国机器人技术的考察,结合多年项目开发实践,本研究采用最先端的人工智能技术来提高机器人的智能化水平。主要研究方向包括,工业机器人、农业机器人、医疗福祉机器人等一系列智能化系统的研究与开发。


陸 慧敏(工学博士)

九州工業大学助教・文部科学省卓越研究員
場所:福岡県北九州市戸畑区仙水町11, E3-209, 804-8550.
E-mail: dr.huimin.luieee.org(@」を「*」に置換してください)

研究内容

(課題1)次世代深海資源調査・開発技術の研究
これまでのビッグデータ・人工知能の研究開発は空中、陸上及び海上等の日常生活支援に関する課題の解決が主である。深海底や大雨時などの極限環境に対する先端的なICT技術や人工知能の研究開発とその応用はまだ不十分であり、従来の人工知能やロボット技術をそのまま適用することが困難な場合が多い。そこで、本研究では世界初の極限環境ロボットに向けたテレロボティクス基盤技術の開発を目的とする。
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(課題2)次世代人工知能(Beyond AI)基盤技術の研究開発
本研究では「単なる」次世代人工知能基盤技術の開発ではなく、日本独自の超知能「Beyond AI」技術を確立することである。これは異なる領域の全ての脳機能と協調し、多様な複雑な問題を解決できる知能学習技術の開発とその応用研究を行う。
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