Click: Call for
Mini-Workshop (W) / Special Session (SS) / Tutorial Session (TS) Proposals.
SPECIAL SESSION (SS):
How to submit in SS?
Click for Special Session - then, click + Create new submission,
then select your Special Session from "SUBJECT AREAS" - starting with 'SS'.
For any query, please e-mail to:
Emi Yuda (Special Session Chair): yuda [use@mark] ieee.org
and CC to -
atiqahad [use@mark] du.ac.bd
Proposed Special Sessions:
SS1: Ionic Polymer Metal Composite - its Application in Engineering
SS2: Ambient Intelligence for Behavior Change
SS3: Artificial Intelligence, Sensing Technology, and Soft Computing
SS4: Acceleration for Deep Learning Models
SS5: Machine Learning in Medical Image Processing and Healthcare Application
SS6: Deep Learning for Pattern Recognition
SS7: Bioimage Informatics in Life Science
SS8: Sensing, Computing and Actuating for Smart Urban Environments
SS9: Information Processing Techniques and the Applications
SS10: Signal and Image Processing for UAVs, Drones, Self-driving Cars, and Robotics
Ionic Polymer Metal Composite (IPMC) - applications towards biosignal capturing, robotic sensor application, micro-gripping application, shape estimation using image processing, mechanical and chemical property analysis of IPMC, application in space research, also use of Electro Active Polymer (EAP) in Engineering.
Srijan Bhattacharya, RCC IIT, India
Email: srijaneie [ATmark] gmail.com
This session deals with research and system related to a behavior
change based on activity recognition. In particular, we focus on a
kind of ambient intelligence, where the surrounding information system
such as digital signage, robots, etc, affects our next behavior.
Yutaka Arakawa, Kyushu University, Japan
Email: arakawa [ATmark] ait.kyushu-u.ac.jp
Yuki Matsuda, Nara Institute of Science and Technology, Japan
Email: yukimat [ATmark] is.naist.jp
Yugo Nakamura, Nara Institute of Science and Technology, Japan
Email: nakamura.yugo.ns0 [ATmark] is.naist.jp
THe session will cover the works relate to Artificial Intelligence, Sensing Technology, and Soft Computing.
Shinji Kawakura, The University of Tokyo, Japan
Emais.kawakura [ATmark] gmail.com
Emi Yuda, Tohoku University, Japan
yuda [ATmark] ieee.org
Implementation of deep learning models are computationally expensive and memory extensive. Deployment in low memory devices with slower GPU, and for applications that required strict latency is the current challenge.
Norliza Mohd Noor, SMIEEE, UTM, Malaysia
Email: norliza [ATmark] utm.my
The emergence of visual data, machine learning algorithms, and advancement in clinical diagnosis has enabled significant breakthrough in vision and healthcare applications. This special issue focuses on medical data, machine learning methods, and applications in image processing, computer vision and related healthcare problems. we strongly encourage authors to submit their original contributions describing their conceptual, algorithmic, methodological, and applications.
Specific topics of interest cover various facets of medical and health care system research, including but not limited to the following:
Medical System, Heath Care System, Human Assist System, Assistive Technology for People with Disabilities, Medical and Health Data Processing, Surgery Support System, Medical Robotics, Medical and Health Data Mining, Medical and Health Big Data Analysis, Health Care System, Health Support System, Telemedicine/Telecare, Nursing system/Telenursing, Wellness support system, Cyberspace application on Medicine, Cyberspace application on Health Care, Cyberspace application on Human Assist, AI in Medicine, AI in Health Care, AI in Human Assist.
Saadia Binte Alam, University of Hyogo, Japan
Email: saadiabinte [ATmark] ieee.org
Pattern recognition involves the automated identification and recognition of pattern and the detection of pattern irregularities. Deep learning is the current state-of-the-art machine learning algorithm that attempt to learn in multiple layers corresponding to different levels of abstraction to solve pattern recognition problems. The advantages of deep learning models are the capabilities to process large amount of data with very high accuracy.
Norliza Mohd Noor, SMIEEE, UTM, Malaysia
Email: norliza [ATmark] utm.my
This session will mainly focus on recent development of computational techniques to analyze biological images and model biological systems. We also welcome papers related to computational analysis of medical image data.
M. Julius Hossain, European Molecular Biology Laboratory (EMBL), Germany
Email: julius.hossain [ATmark] embl.de
M. Ali Akber Dewan, Athabasca University, Canada
Email: adewan [ATmark] athabascau.ca
Sensors and actuators are leaving lab environments and enter the domestic, office, shopping, public, recreational and urban environments. These environments track human behavior, adapt to human behavior or persuade or enforce humans to adapt their behavior to the environment. In urban environments sensors and actuators can be designed in order to make such environments more efficient and manageable. Smart cities aim at using digital smartness to improve waste management, reduce energy consumption, increase safety, control traffic and improve public transport et cetera. Drones, delivery robots, and self-driving cars will complete the future urban landscape. Digital smartness obtained by sensors and actuators can also help to make a city more attractive by introducing entertaining applications and allowing game-like applications of such technology in the urban environment.
In this special session, we ask for papers that address these issues. Papers can discuss scientific, engineering and societal issues related to applications made possible by introducing sensors, actuators and computer processing in urban environments.
Anton Nijholt, University of Twente, The Netherlands
Email: a.nijholt [ATmark] utwente.nl
Md Atiqur Rahman Ahad, Osaka University, Japan; Univerity of Dhaka, Bangladesh
Email: atiqahad [ATmark] du.ac.bd
M. Abdullah-Al-Wadud, King Saud University, Saudi Arabia
Email: mwadud [ATmark] ksu.edu.sa
This special session will showcase recent advances on signal and image processing for UAVs, Drones, IoT, Autonomous Vehicles and Robotics. A special journal issue will be launched after the conference.
Chowdhury Shahriar, Northrop Grumman Corporations, USA
Email: cshahria [ATmark] vt.edu
We welcome you to organize Mini-Workshop / Special Session / Tutorial Session!
The aim of a W/SS/TS is to provide a complementary flavor to the regular sessions and should include hot topics of interest to the conference topics that may also go beyond disciplines traditionally represented at the conference.
Prospective organizers of W/SS/TS should submit proposals with the info below:
- Title of the W/SS/TS:
- Objective of the W/SS/TS: Define & explain - how the W/SS/TS will be different/related from the subjects covered by the regular sessions.
- Name of the W/SS/TS organizers and short profiles of them.
- Information on possible papers, presenters and apart from papers to be presented, mention whether you will invite any speaker for the W/SS/TS.
[Minimum number of papers for a SS: 4 accepted papers at least and no compromise on quality!]
- Mini-Workshop length: Half-day workshop may be allowed.
W/SS/TS's evaluation criteria:
All papers presented in the W/SS will be included in the Conference Proceedings.
Therefore, all papers must submit according to the instructions of the conference.
- Interest on the topic
- Evaluation on the organizers [& panel of experts reviewers for W/OS]
- Plan of the W/SS/TS
Don't miss this opportunity to attend this conference!
We are looking forward to have you in the conference!