Call for Papers
SUMAC 2020 – The 2nd workshop on Structuring and Understanding of Multimedia heritAge Contents
In conjunction with ACM Multimedia 2020
12 – 16 October 2020, Seattle, United States
https://sumac2020.ec-lyon.fr
https://2020.acmmm.org
*** Aims and scope
The digitization of large quantities of analogue data and the massive production of born-digital documents for many years now provide us with large volumes of varied multimedia data (images, maps, text, video, multisensor data, etc.), an important feature of which is that they are cross-domain. "Cross-domain" reflects the fact that these data may have been acquired in very different conditions: different acquisition systems, times and points of view (e.g. a 1962 postcard from the Arc de Triomphe vs. a recent street-view acquisition by mobile mapping of the same monument). These data represent an extremely rich heritage that can be exploited in a wide variety of fields, from SSH to land use and territorial policies, including smart city, urban planning, tourism, creative media and entertainment. In terms of research in computer science, they address challenging problems related to the diversity and volume of the media across time, the variety of content descriptors (potentially including the time dimension), the veracity of the data, and the different user needs with respect to engaging with this rich material and the extraction of value out of the data. These challenges are reflected in research topics such as multimodal and mixed media search, automatic content analysis, multimedia linking and recommendation, and big data analysis and visualisation, where scientific bottlenecks may be exacerbated by the time dimension, which also provides topics of interest such as multimodal time series analysis.
The objective of the second edition of this workshop is to present and discuss the latest and most significant trends in the analysis, structuring and understanding of multimedia contents dedicated to the valorization of heritage, with emphasis on the unlocking of and access to the big data of the past. We welcome research contributions related to the following (but not limited to) topics:
- Multimedia and cross-domain data interlinking and recommendation
- Dating and spatialization of historical data
- Mixed media data access and indexing
- Deep learning in adverse conditions (transfer learning, learning with side information, etc.)
- Multi-modal time series analysis, evolution modelling
- Multi-modal and multi-temporal data rendering
- HCI / Interfaces for large scale data sets
- Smart digitization of massive quantities of data
- Benchmarking, open data movement
*** Important dates
Submission Due: Monday 29 June 2020 (11:59 p.m. AoE)
Author acceptance notification: 27 July 2020
Camera Ready Submission: 7 August 2020
Workshop Date: 12 or 16 October 2020 (TBA)
*** Submission guidelines
Submission format. All submissions must be original work not under review at any other workshop, conference, or journal. The workshop will accept papers describing completed work as well as work in progress. One submission format is accepted: full paper, which must follow the formatting guidelines of the main conference ACM MM 2020. Full papers should be from 6 to 8 pages (plus 2 additional pages for the references), encoded as PDF and using the ACM Article Template. For paper guidelines, please visit: https://2020.acmmm.org/call-for-paper.html
Peer Review and publication in ACM Digital Library. Paper submissions must conform with the “double-blind” review policy. All papers will be peer-reviewed by experts in the field, they will receive at least two reviews. Acceptance will be based on relevance to the workshop, scientific novelty, and technical quality. Depending on the number, maturity and topics of the accepted submissions, the work will be presented via oral or poster sessions. The workshop papers will be published in the ACM Digital Library.
*** Organizers
Valérie Gouet-Brunet (LaSTIG Lab / IGN – Gustave Eiffel University, France)
Liming Chen (LIRIS Lab / Centrale Lyon, France)
Xu-Cheng Yin (University of Science and Technology Beijing, China)
Ronak Kosti (Pattern Recognition Lab / FAU Erlangen-Nürnberg, Germany)
Margarita Khokhlova (LaSTIG/LIRIS Labs, IGN & Centrale Lyon, France)
Looking forward to seeing you in Seattle!
The workshop organizers
Conferences lSCMl
April 14th, 2020 
Daniela Lopez de Luise Dear esteemed colleagues,
Warm greetings from India. Hope you and your loved ones are doing well. Pls. take care.
2020 lSCMl, the annual flagship event of llCCl http://www.iicci.in/ ), to be held in Stockholm, Sweden (14th-15th Nov, 2020) http://iscmi.us/index.html
IEEE Sweden Section, IEEE Computational Intelligence Society & IFSA are the technical co sponsors for the same.
This is to gently remind you that the paper submission deadline for the same is little less than 3 months away (25th June, 2020).
Till now the proceedings of all the previous 6 lSCMl conferences were successfully uploaded at IEEE Xplore.
Since 2017, lSCMl is being held annually in memory of life & work of Prof. Lotfi Zadeh.
For 2020, The annual llCCl Prof. Zadeh Memorial lecture would be delivered by Prof. B-M Bernadette, the current President of IEEE Computational Intelligence Society (Life Fellow, IEEE & also Fellow, IFSA).
Apart from the lEEE published proceedings & uploading of the same at Xplore, scope of a selected subset of papers for being considered for publications at the special issue of the NCAA journal (a Springer publications having 2018 Impact Factor & 5 year Impact Factor of 4.664 & 3.570 respectively https://www.springer.com/journal/521) also exist.
You are warmly invited to submit your research findings for this conference.
Hope to welcome & meet many of you in Stockholm this year.
Thanks so much & kind rgds,
Suash
(Prof. Suash Deb) General Chair, ISCMI20 (Stockholm, Sweden)
Advances in AI and Machine Learning: Addressing Risks and Concerns, IEEE Intl Workshop at COMPSAC (virtual conference), July 2020 — CALL for PAPERS
April 14th, 2020 Daniela Lopez de Luise 
July 13-17, 2020
This year COMPSAC will take place virtually.
Third IEEE International Workshop on
Advances in Artificial Intelligence and Machine Learning (AIML):
Addressing Risks and Concerns
Call for Papers
Submissions Due: 24 April 2020
https://ieeecompsac.computer.org/2020/aiml/
Artificial intelligence (AI) is finally starting to deliver real-world benefits, and early adopters in businesses and industry in several sectors are embracing the promise of AI reaping significant benefits. On the downside, like any new technology, AI presents risks, raises concerns regarding its safety and societal impact, and poses development and implementation challenges. To reap fuller potential of AI, we must satisfactorily address these shortcomings.
This 3rd IEEE International Workshop on Advances in AI and Machine Learning (AIML) aims to examine risks and concerns of AI and machine learning (ML) and showcase scientific, technical and practical advances in addressing them. The workshop will also highlight recent advances in AI and ML and their applications, cover AI strategy and policy, examine development and deployment challenges, and discuss concepts such as AI for good, Responsible AI, and Explainable AI. It is an interactive forum for AI researchers, practitioners and business executives for discussion on key issues and challenges and practices related to AI applications, and for sharing case studies and application experience.
Researchers and practitioners from all over the world, from academia, industry, and government are invited to present their work, perspectives, experiences and vision, and participate in the workshop.
Topics of interest include, but are not limited to:
- Advances in AI and machine learning, deep learning, cognitive computing, intelligent agents, chatbot
- AI strategy for business and industry
- AI applications in industry, business, healthcare, and education and training
- AI in government and legal practice
- Entertainment in the age of AI
- AI for enhancing information security and privacy
- Work in the age of AI
- Trust, resilience, privacy and security issues in AI applications
- Testing and validation of AI and ML applications
- Risks, limitations, and challenges of AI and ML
- Legal, regulatory, ethical aspects of AI (liability, etc.)
- AI: promise vs practice
- Societal implication of the rise of AI
- Human-machine co-existence and collaboration
- Intelligent, autonomous robots and cars
- Industry 4.0
- Smart society
- AI and IoT
- Case studies, experience reports, position papers and visionary perspectives
- Overview of AI activities in a region/country
- The Future of AI
Authors are invited to submit original, unpublished papers.
Simultaneous submission to other publication venues is not permitted. In accordance with IEEE policy, submitted manuscripts will be checked for plagiarism; instances of alleged misconduct will be handled according to the IEEE Publication Services and Product Board Operations Manual.
For detailed instructions on submission see Information for Authors at https://ieeecompsac.computer.org/2020/.
Submissions Due: 24 April 2020
Workshop organizers
San Murugesan, Director BRITE Professional Services; Editor in Chief Emeritus,
IEEE CS IT Professional, Australia, san1@internode.net
Yunji Liang, Northwestern Polytechnical University, P.R.China, liangyunji@nwpu.edu.cn
Piyush Saxena, Direct Supply, USA, piyush.saxena.phd@gmail.com
Lia Morra, Politecnico di Torino, Italy, lia.morra@polito.it
ICFHR 2020 Competition on Thai Student Signature and Name Component Identification and Verification – Call for Participation
April 14th, 2020 Daniela Lopez de Luise Details about the competition can be found on: http://sasigcomp2020.chefitup.club/art.suwanwiwat/
Please find a call for participation flyer attached with this email. Researchers working on handwriting recognition research and applications and biometrics are strongly invited to participate in this competition.
Register is now open, please follow instruction on the website to register. The datasets will be released soon on the TC10/11 website.
Kindly, please circulate this invitation to your colleagues who might be interested in this competition.
Best regards
SASIGCOM Organisers
Hemmaphan Suwanwiwat (James Cook University)
Abhijit Das ( ISI, Kolkata, India )
Umpada Pal (ISI, Kolkata, India)
Michael Blumenstein (UTS, Australia)
Urgent Call for Chapters – Data Science for COVID-19 (Elsevier)
April 14th, 2020 Daniela Lopez de Luise (Edited by Utku Kose, Deepak Gupta, Victor Hugo C. de Albuquerque, Ashish Khanna)
to be published by Elsevier
COVID-19 is currently the most dangerous variation of the coronavirus as threating the humankind, accepted as the pandemic by the World Health Organization (WHO). Nowadays, there is not almost any country where issues regarding COVID-19 is not observed. With thousands of reported deaths and the cases more than that, the world is in an active war to eliminate that virus. In the past, such situation had already been experienced with important viruses such as Ebola, H1N1, and Influenza. However, the most devastating results within last two centuries may will be associated with the active COVID-19. While the sub-fields medical as well as natural sciences have been working instantly on deriving solutions and trying to protect the humankind against such virus types, there is also a great focus on technological developments for improving the mechanism – momentum of science for effective and efficient solutions. At this point, Data Science is the most powerful tools for researchers to fight against COVID-19. Thanks to instant data-analyze and predictive techniques by the Data Science, it is possible to get positive results and introduce revolutionary solutions against the related medical diseases. By running capabilities – resources for rising the Data Science, technological fields like Artificial Intelligence (with Machine / Deep Learning), Data Mining, Applied Mathematics are essential components for processing data, recognizing patterns, modeling new techniques and improving the advantages of the Data Science more. Nowadays, there is a great interest in application potentials of the Data Science so that it will be an effective approach for taking the humankind more step away, after COVID-19 and also before pandemics similar to the COVID-19 many appear.
The main goal of the proposed edited book: ‘Data Science for COVID-19’ is to provide the most recent research and innovative developments regarding the COVID-19. In this context, the book aims to inform the target audience about the latest findings-results regarding a wide variety of Data Science applications for fighting COVID-19.
There is currently a great emergency state in all over the world and the scientific audience is looking for instant solutions and further works to eliminate all cases of COVID-19 problems and similar pandemics that may threaten the humankind in the future. Moving from that, alternative applications of Data Science are too valuable and critical. Such applications can be done over data such as medical image, raw data, statistical findings, and even ongoing real-time rates in terms of active pandemic cases, deaths, treated people and potential components such as animals as the origin of such pandemics.
Submission Guidelines:
All submissions should be done by email to: utkukose@gmail.com and / or deepakgupta@mait.ac.in and / or victor.albuquerque@unifor.br and / or ashishkhanna@mait.ac.in
Please consider the rules here while preparing the full chapter: https://booksite.elsevier.com/brochures/authors/Text/type.htm
All papers must be original and not simultaneously submitted to another book project, journal or conference. The following important dates will be considered for the submissions:
- Full Paper Submission: 30.04.2020
- Notification of Accept / Reject: 05.05.2020
- Final Chapter Due: 10.05.2020
List of Topics (as not limited to):
- COVID-19 virus with their essentials as a treat,
- Image Analysis and Processing for COVID-19,
- Design of Cognition and Computing for COVID-19,
- Data Processing for COVID-19,
- Geoprocessing / Tracking for COVID-19,
- Diagnosis for COVID-19,
- Laboratorial Data Analysis for COVID-19,
- Predictive Systems for COVID-19,
- Mobile technology solutions for COVID-19,
- Artificial Intelligence based solutions for COVID-19,
- Treatment of for COVID-19 with Data Science,
- Public Safety for COVID-19,
- Governmental Applications for COVID-19,
- Data Science Policies for COVID-19,
- Internet of Health Things (IoHT) for COVID-19,
- Big Data for COVID-19,
- New Data Models for COVID-19,
- …etc.
It is important that research works with only targeting COVID-19 will be given more emphasis while a few of alternative works giving insights for potential pandemics will be accepted. Also, the contributors will be encouraged to provide also success stories, negative results and experiences / feedback they received from physicians and medical staff.
Editors:
Utku Kose, PhD. (Suleyman Demirel University, Turkey)
Deepak Gupta, PhD. (Maharaja Agrasen Institute of Technology, India)
Victor Hugo C. de Albuquerque (Universidade de Fortaleza, Brazil)
Ashish Khanna, PhD. (Maharaja Agrasen Institute of Technology, India)
'Data Science for COVID-19' will be published by Elsevier.
Contact:
All questions about submissions should be e-mailed to: utkukose@gmail.com
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