Speakers

Keynote Speaker 

Professor Wendong Xiao

University of Science and Technology Beijing, China     

Prof. Wendong Xiao is currently a Professor with the School of Automation and Electrical Engineering, University of Science and Technology Beijing, P. R. China. His previous appointments include Scientist III with the Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore (2004-2012), Research Fellow with the Nanyang Technological University, Singapore (2001-2004), Associate Professor with the Northeastern University, China (1999-2001), and Post-Doctorate Research Fellow with the POSCO Technical Research Laboratories, South Korea (1996-1999). He received his Ph.D. degree from Northeastern University, China in 1995. His current research focuses on wireless localization and tracking, energy harvesting based network resource management, wearable computing for healthcare, big data processing, wireless sensor networks and internet of things. He has published about 150 papers in Journals and conferences and has been participating in a number of research and industrial projects in the related areas. He has been actively participating in the organizations for more than 70 international conferences and reviews for many top international Journals.

Keynote Speaker 

Professor Jianquan Ouyang

Xiangtan University, China      

Ouyang Jianquan, Ph.D., Second-level professor of Hunan Province, doctoral supervisor, visiting scholar at the University of Georgia, U.S.A. He was selected as the third-level candidate of Hunan Province New Century 121 Talent Project in 2011. He was selected as the 2019-2020 Hunan Province "Three Districts" Talent Support Program. He was awarded the China Industry-University-Research Cooperation Promotion Award in 2019. He was awarded the Baosteel Education Award and the first outstanding science and technology worker in Xiangtan City in 2018. He was awarded the third prize of Hunan Province Natural Science in 2010. He was awarded the second prize of Hunan Province Teaching Achievement in 2013 and the second prize in 2016 and 2019. In 2014, he won the third prize of excellent achievements in educational scientific research in Hunan Province. In 2018, he won the national prize of teaching innovation in artificial intelligence and big data education in colleges and universities. In 2020, 2021 and 2022, he won the "Outstanding Contribution Award" for Artificial Intelligence Big Data Blockchain Education in National Universities. In 2007, he was selected as the training object of young backbone teachers in general colleges and universities in Hunan Province. He is a senior member of China Computer Federation (CCF) and a liaison of Xiangtan University, a correspondent member of CCF Youth Working Committee, a member of CCF Education Working Committee, a correspondent member of CCF Big Data Expert Committee, a standing member of CCF Computer Application Professional Committee, a member of CCF Computer Vision Professional Committee, a member of CCF Pervasive Computing Professional Committee, a member of YOCSEF ( Young Computer Science and Technology Forum of Chinese Computer Society) Changsha Sub-Forum 2015-2016 Chair, Executive Member of CCF Changsha Member Center, Senior Member of Chinese Society of Artificial Intelligence.

Title: Combination of U-Net and Region Growing is needed for Sperm Segmentation

Abstract: Accurate segmentation methods for sperm are always important prerequisites for automatic sperm morphological analysis, which is a crucial part of male infertility diagnosis. However, existing methods can only handle well on the part of the sperm head, due to their more regular shapes. In another word, Such manners will leave out the tail parts when performing segmentation, thus leading to inaccurate sperm morphological analysis. Specifically, previous deep learning U-Net cannot perform well with such limited sperm tail data. Meanwhile, the traditional region-growing methods cannot handle the area where there is a break due to picture quality, which raises higher requirements for seed selection. To this end, we propose a unified segmentation framework, termed URS, which makes use of the advantages of both deep learning and traditional region-growing methods. More concretely, we first perform bilateral filtering operations and histogram equalization on the sperm microscopic images to make the sperm images more discriminative. Then, we adopt a specific U-Net structure with Leaky ReLU. Besides, an adaptive seed selection region growing algorithm is designed in this paper, which selects seeds based on the sperm skeleton iteration by iteration until no new seeds are found. The proposed method can get promising segmentation performance for both sperm head and sperm tail. Since there is no open-source sperm segmentation dataset, especially for the sperm tail. Thus, a novel dataset is also contributed to this paper. We evaluate our framework on a sperm segmentation dataset and obtained Dice of 0.92, 0.81, and 0.86 for sperm head, sperm tail, and the whole sperm, respectively. Extensive experiments, i.e., case study, ablation study, and parameter analysis, demonstrate that our framework outperforms other existing methods, especially for sperm tail segmentation.

Keynote Speaker 

Professor  KANNIMUTHU SUBRAMANIYAM

Karpagam College of Engineering, Anna University, Chennai, India

Bio: Kannimuthu Subramaniyam is currently working as Professor in the Department of Computer Science and Engineering at Karpagam College of Engineering, Coimbatore, Tamil Nadu, India. He is also an In-Charge for the Center of Excellence in Algorithms. He is an IBM Certified Cybersecurity Analyst. He did PhD in Computer Science and Engineering at Anna University, Chennai. He did his M.E (CSE) and B.Tech (IT) at Anna University, Chennai. He has more than 15 years of teaching and industrial experience. He is the recognized supervisor of Anna University, Chennai. Two PhD candidate is completed their research under his guidance. He is now guiding 7 PhD Research Scholars. He has published 54 research articles in various International Journals. He published 2 books ("Artificial Intelligence" & “LinkedList Demystified-A Placement Perspective” and 3 Book Chapters (WOS / Scopus Indexed). He is acting as mentor / consultant for DeepLearning.AI, Hubino, MaxByte Technologies and Dhanvi Info Tech, Coimbatore. He is the expert member for AICTE Student learning Assessment Project (ASLAP). He has presented a number of papers in various National and International conferences. He has visited more than 75 Engineering colleges and delivered more than 125 Guest Lectures on various topics. He is the reviewer for 35 Journals and 3 Books. He has successfully completed the consultancy project through Industry-Institute Interaction for ZF Wind Power Antwerpen Ltd., Belgium. He has received funds from CSIR, DRDO and ISRO to conduct workshops and seminars. He has completed more than 610 Certifications (41 Specializations and 4 Professional Certifications) in Coursera, Hackerrank and NPTEL on various domains. He has guided a number of research-oriented as well as application-oriented projects organized by well-known companies like IBM. He is actively involving in setting up lab for Cloud Computing, Big Data Analytics, Open-Source Software, Internet Technologies etc., His research interests include Artificial Intelligence, Data Structures and Algorithms, Machine Learning, Big Data Analytics, Virtual Reality & Blockchain.