SCOPUS-CGIIT 2021 : 5th International Conference on Graphics, Images and Interactive Techniques (CGIIT 2021)
Call For Papers
5th International Conference on Graphics, Images and Interactive Techniques (CGIIT 2021)
Feb. 25-28, 2021 | Auckland, New Zealand
5th International Conference on Graphics, Images and Interactive Techniques (CGIIT 2021) is the joint conference of CMVIT 2021, which is organized by Federation University Australia, and technically sponsored by Shanghai Jiaotong University and Xi’an Jiaotong-Liverpool University. The conference will be hosted in Auckland, New Zealand from Feb 25 to 28, 2021!
We warmly welcome prospective authors to submit your research papers to CGIIT 2021, and share your latest research results and valuable experiences with other top-scientists, engineers and scholars from all over the world.
●Publication and Indexing
All the registered and presented papers will be published in the volume of conference proceeding, which will be submitted to Engineering Village, Scopus, Thomson Reuters (WoS) and other databases for review and indexing.
●CGIIT 2021 Speakers
Prof. Cheng-Lin Liu, Institute of Automation of Chinese Academy of Sciences, China
Fellow of the CAAI, IAPR and the IEEE, Director of National Laboratory of Pattern Recognition (NLPR), Vice President of Institute of Automation of Chinese Academy of Sciences. His research interests include pattern recognition, image processing, neural networks, machine learning, and especially the applications to character recognition and document analysis. He has contributed many effective methods to different aspects of handwritten document analysis, including image pre-processing, page segmentation, feature extraction, classifier design, and character string recognition. His algorithms have yielded superior performance, and have been transferred to industrial applications including mail sorting, form processing and Web document retrieval.
Prof. Peter Han Joo Chong, Auckland University of Technology, New Zealand
Professor Peter Han Joo Chong is an Associate Head of School (Research) and a Head of Department of Electrical and Electronic Engineering (EEE) at Auckland University of Technology, New Zealand. He is currently an Adjunct Professor at the Department of Information Engineering, CUHK. His current research projects focus on machine learning techniques applied to 5G vehicularnetworks. He has been developing techniques of deep reinforcement learning (DRL)-based resource management for future 5G Cellular-V2X networks.
Prof. Donald Bailey, Massey University, Palmerston North, New Zealand
Donald Bailey is currently Professor of Imaging Systems at Massey University, and is co-director of the Centre for Research in Image and Signal Processing. Donald has spent over 35 years applying image processing technology to a range of industrial, machine vision and robot vision applications. He is the author of many publications in this field, including the book “Design for Embedded Image Processing on FPGAs”, published by Wiley / IEEE Press. He is a Senior Member of the IEEE, and is active in the New Zealand Central Section. He is currently chair of the IEEE New Zealand Council.
●Topics(for more topics:http://www.cgiit.org/cfp.html)
Advanced image processin
Visualization, Virtual Reality and Augmented Reality
Social networks interaction
User interfaces for multitudes
Massive interaction platforms
Electronic submission system: https://cmt3.research.microsoft.com/CGIIT2021
●Call for participants
1,Presenter:If you are interested in giving presentation on conference,without publishing your paper in the proceeding,you need to submit the abstract and title of your presentation to us:CGIIT_conference@163.com
2,Listener:You are welcome to attend this great event. You need to complete the registration as Listener before the registration dealdine.
3,Reviewer:We sincerely welcome professors, associate professors, teachers and other experts in the areas of Graphics, Images and Interactive Techniques join the conference as a reviewer.
Ms. Con Cong
Tel:+852-30506939(Tel) | +86-17723329879 (Phone)