CFP: Multimedia Datasets for Repeatable Experimentation (MDRE’21) at MMM’21

June 27th, 2020 Daniela Lopez de Luise
Call for Submissions

Special Session on “Multimedia Datasets for Repeatable Experimentation (MDRE)”
MMM 2021 – 27th International Conference on Multimedia Modeling
January 25-27, 2021 @ Prague, Czech Republic

Information retrieval and multimedia content access has a long history of comparative evaluation and many of the advances in the area over the past decade can be attributed to the availability of open datasets that support comparative and repeatable experimentation. Sharing data and code to allow other researchers to replicate research results is needed in the multimedia modeling field and helps to improve the performance of systems and the reproducibility of published papers. 

The MDRE’21 special session at MMM 2021, the third in the MDRE series, presents an opportunity for researchers and practitioners to submit their datasets to this track, making their work permanently available and citable via the http://mmdatasets.org forum, as well as to increase the public awareness of their considerable efforts. Together with the dataset, authors are asked to provide a paper describing its motivation, design, and usage, a brief summary of the experiments performed to date on the dataset, as well as discussing the way it can be useful to the community.  We may additionally accept a small number of position papers of high quality, which we believe can significantly impact multimedia datasets in the future, by addressing various aspects of the dataset creation and release process. We will prefer position papers that are backed up by recent results, which could be already published or appear first in the MDRE submission. 

We seek high-quality submissions of length up to 12 pages. We invite a variety of submissions to the special session:
  • Dataset papers: These papers should present recent and impactful datasets that would be of interest to the MMM community.
  • Position papers: These papers can address various aspects of the creation, release or use of multimedia datasets. 

All papers must represent original and unpublished work that is not currently under review. 

Special session papers will supplement the regular research papers and will be included in the proceedings of MMM 2021 and the datasets will be indexed by the MDRE website (http://mmdatasets.org). 

Submissions:
Submissions will follow the exact same author guidelines of MMM 2021. The conference proceedings will be published in the series of Lecture Notes in Computer Science (LNCS) by Springer. Submissions must not exceed 12 pages and must conform to the formatting instructions of Springer Verlag, LNCS series, and adhere to the submission schedule. Regular research paper submissions will be peer-reviewed in a double-blind review process; thus, the submissions must be properly anonymised. Each contribution must be associated with one full registration; only one contribution can be associated with each registration. The submission site can be found here: https://easychair.org/my/conference?conf=mmm2021

Regarding the submission of a paper describing a new MM dataset, the authors are encouraged to make it available by providing a public URL on the MDRE dedicated site that archives outputs of the MDRE special sessions. All datasets described must be licensed in such a manner that it can be legally and freely used with all appropriate ethical approvals completed. Authors are encouraged to prepare appropriate and helpful documentation to accompany the dataset submissions, including examples of how it can be used by the community, examples of successful usage and restrictions on usage. 

Why Submit to the MDRE Special Session?
– Accepted contributions will be included in the MMM conference proceedings, as part of the Lecture Notes in Computer Science (LNCS) series by Springer. Authors of selected  MMM papers will be invited to publish extended versions in a journal special issue.
– Accepted contributions will be listed in the new archive of MDRE multimedia datasets and frameworks (http://mmdatasets.org), thereby increasing their visibility.
– Authors of accepted contributions will be invited to present their dataset (or framework) as part of the special session at MMM 2021.
– MDRE is planned to be an annual special session at the MMM conference series.
Important Dates:
Submission Deadline: July 12, 2020
Notification of Acceptance: September 20, 2020
Camera-ready submissions: October 18, 2020

Session organizers:
– Cathal Gurrin (Dublin City University)
– Duc-Tien Dang-Nguyen (Dublin City University)
– Klaus Schoeffmann (Klagenfurt University)
– Björn Þór Jónsson (IT University of Copenhagen)

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1st International Workshop on Artificial Intelligence and Robotics for Law Enforcement Agencies

June 27th, 2020 Daniela Lopez de Luise

We cordially invite you to attend and submit your papers to the AIRLEAs workshop which will be held in conjunction with 3rd International Conference on Intelligent Technologies and Applications (INTAP'20)  on 28th -30th  September, 2020 and hosted by the Norwegian University of Science & Technology (NTNU), Norway. AIRLEAs and INTAP2020 are organized by NTNU, Gjovik, Norway, University of Agder, Norway and Artificial Intelligence Research Group, IUB.  Also, INTAP'20 will be technically sponsored by Springer and co-sponsored by IEEE Norway Section.

 

All accepted and presented papers will be published by CCIS-Springer and indexed in Scopus and Web of Science.  Extended version of the selected papers will appear in the special issues of the following peer reviewed journals — Computers and Electrical Engineering by Elsevier, SAGE Open Journal – indexed in SCI, Special Collection on Artificial Intelligence for IoT Systems (IJDSN and Scopus Journal of Telecommunication, Electronic and Computer Engineering (JTEC).

 

Topics of interest for AIRLEAs include, but are not limited to:

  1. AI and robotics opportunities for LEAs
  • Artificial Intelligence and robotics for LEAs in the EU.
  • Big data, analytics and AI for LEAs.
  • Human robot interaction.
  • Computer forensics readiness through Artificial Intelligence.
  • Forensics data analytics.
  • Automated reasoning in cybercrime investigations.
  1. Policy and regulatory perspective
  • Perspectives from GDPR and Directive on data protection in law enforcement (EU) 2016/680.
  • Legal, ethical and societal aspects of AI and robotics technologies in LEAs.
  • Integrating law and policy compliance into the development process.
  • Fairness, accountability, transparency, explainability features etc..
  1. Technical and Organizational Measures for Privacy and Security
  • Privacy and Data Protection-by-design.
  • Privacy-enhancing technologies (PETs).
  • Privacy engineering in AI and robotics technologies.
  • Privacy engineering and data subject rights.
  • Privacy or data protection impact assessments in the context of AI and robotics technologies.
  • Partially and Fully Homomorphic Encryption.
  • Use-Case scenarios with homomorphic encryption libraries (SEAL, HElib, TFHE).
  • Privacy and anonymity.
  1. Ethical principles and ethical guidelines for the design, use, and operation of application
  • Standards for the Ethics of AI and robotics.
  • Ethics by Design.
  • Ethics of algorithms & artificial
  • Bias in algorithmic decision-making.
  • Ethics of algorithms & AI.
  • Ethics of data collection and algorithmic processes.
  1. Privacy and security training and education for LEAs
  • Awareness and effectiveness of educational training.
  • Policies and procedures training.
  • Privacy and data privacy awareness Training
  • Teaching and training privacy engineering.

 

We shall be looking forward to your paper contributions and participation. We hope that attending the conference and the workshop will provide an opportunity to meet academic and industry experts to exchange ideas about the latest technologies. We are sure that your stay in the beautiful city of Gjøvik will be very pleasant and enjoyable.

Best Regards,
AIRLEAs & INTAP’20 organizing committee

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Call for Book Chapters: Tensors in Data Processing published by Elsevier

June 27th, 2020 Daniela Lopez de Luise

We are working together with Elsevier to publish a book tentatively entitled Tensors for Data Processing. 

The aim is to provide principles and methods and state of the art research for undergraduates, graduates, researchers and practitioners. It will be available in print and electronically. The book’s topics of interest includes, but are not limited to:

1. tensor for data processing challenges

2. fundamentals on tensor computation

3. introduction on tensor decomposition

4. tensor completion

5. tensor subspace clustering

6. tensor subspace tracking

7. tensor graphical model

8. tensor neural networks

9. tensor regression

10. multilinear discriminative component analysis

11. tensor independent component analysis

12. tensor principal component analysis

13. linked tensor component analysis

14. coupled tensor for data fusion

15. compressive sensing of tensor

16. tensor for blind source separation

17. tensor for image segmentation

18. tensor for image registration

19. tensor for feature extraction

20. tensor for image’s quality assessment

21. tensor for recommender systems

22. tensor for wireless communication

23. tensor for wireless location

24. tensor for radar

25. tensor for computational imaging

26. tensor for multi-view image clustering

27. tensor for speech and audio processing

28. tensor for neuroimage

29. tensor for biomedical monitoring


Elsevier reports that books on principles and methods are highly used in electronic form by students and researchers who are able to download chapters through their library. They are also the type of books most bought in print form, and are most cited. All individual chapters will be indexed by Google Scholar and Scopus.


As you are a recognized excellent expert in this field, we cordially invite you to contribute a book chapter on this topic providing an explanation of the principles, methods and applications. Note that the chapter topic is tentative and you are welcome to suggest a different title or a different but related topic.


Although this book is an edited volume, it will be tightly integrated as a cohesive whole, with a common specification.


Please feel free to contact me, if you are interested in it, please.


Best Regards,


Yipeng

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CFP: PRL Virtual Special Issue: I Implicit BIOmetric Authentication and Monitoring through Internet of Things

June 27th, 2020 Daniela Lopez de Luise
Pattern Recognition Letters – Special Issue on Implicit BIOmetric Authentication and Monitoring through Internet of Things – VSI acronym: I-BIO
Motivations
According to reliable forecasts, the expected number of connected IoT devices could exceed 25 billions by 2020. An important fraction of this number includes last generations mobile and wearable devices featuring an arsenal of advanced sensors (high speed/depth/multi-focal cameras, finger imaging, accelerometers, gyros, etc.), up to 5G communication capability and growing computing power. This collection of features makes them particularly suited to capture both static and dynamic biometrics, to continuously monitor health signals and/or to provide information about the operating context. In summary, these capabilities will enable a new generation of Internet of Biometric Things (IoBT) approaches which will greatly extend the range and the target of “mainstream” biometric applications. This Special Issue aims at gathering the latest research findings and applications for transparent acquisition and processing of biometrics and health signals in the context of ubiquitous IoBT-based user authentication and monitoring, outlining new application scenarios for mobile biometrics. 
List of Topics
Topics include, but are not limited to:
• IoBT enabled biometrics
• Ubiquitous user authentication/recognition
• Ubiquitous biometric monitoring
• Implicit IoBT-enabled authentication/recognition
• Implicit IoBT-enabled activity recognition
• Implicit IoBT-enabled context detection
• Dynamic biometrics capture and processing
• Implicit psychophysical assessment
• Deep Learning for IoBT applications
• Health signals analysis via mobile devices
• Elders monitoring through IoBT devices and approaches
• Privacy and IoBT
Important Dates
Start of submission period: September 1, 2020
Deadline for submission: September 30th, 2020 First review notification: December 1st, 2020 Revision submission: January 15th, 2021
Second review notification: February 15th 2021 
All submissions in final status: March 31st 2021
Submission Guidelines
All submissions have to be prepared according to the Guide for Authors as published in the Journal Web Site at http://www.elsevier.com/journals/pattern-recognition-letters/0167-8655/guide-for-authors.
Submissions should be sent through http://ees.elsevier.com/prletters/. Authors should select the acronym “VSI:I-BIO” as the article type, from the “Choose Article Type” pull-down menu during the submission process.
The maximal length of a paper is 7 pages in the PRLetters layout and may become 8 in the revised version if referees explicitly request significant additions.
The submitted papers should not have been previously published or be under consideration for publication elsewhere. If one submission is the extended work of one conference paper, the original work should be included and a description of the changes should be provided.
The PRLetters submission should include at least 30% new contribution of high relevance (more experiments, proofs of theorems not included in the conference paper, more comparisons with other methods in the literature and so on); and the title of the PRLetters paper should be different, the same figures cannot be used and the common part of the conference paper and of the extended version cannot be verbatim the same. 
Review Process
The review process will follow the standard PRLetters scheme. Each paper will be reviewed by at least two referees and that, in general, only two reviewing rounds will be possible, out of which major revision is possible for the first reviewing round. Submissions will probably be rejected if major revision is still required after the second reviewing round. 
Contacts
For inquiries regarding the special issue, send an email to the managing guest editor at: stefano.ricciardi@unimol.it 
Guest Editors
Stefano Ricciardi (Managing Guest Editor), University of Molise, Italy. E-mail: stefano.ricciardi@unimol.it
Modesto Castrillón-Santana (Guest Editor), University of Las Palmas de Gran Canaria, Spain.  E-mail: modesto.castrillon@ulpgc.es
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CIS Webinar – A Rigorous Analysis of Self‐Adaptation in Discrete Evolutionary Algorithms (Joint Work with Brendan Case)

June 26th, 2020 Daniela Lopez de Luise

;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:#ffffff;text-decoration-style:initial;text-decoration-color:initial”>Biography:

Per Kristian Lehre is a Senior Lecturer at the University of Birmingham, UK. He received MSc and PhD degrees in Computer Science from the Norwegian University of Science and Technology (NTNU). After finishing his PhD in 2006, he held postdoctoral positions in the School of Computer Science at the University of Birmingham and at the Technical University of Denmark. From 2011, he was a Lecturer in the School of Computer Science at the University of Nottingham, until 2017, when he returned to Birmingham. Dr. Lehre's research interests are in theoretical aspects of nature‐inspired search heuristics, in particular, runtime analysis of population‐based evolutionary algorithms. His research has won several best paper awards, including at GECCO (2013, 2010, 2009, 2006), ICSTW (2008), and ISAAC (2014). He is an editorial board member of Evolutionary Computation and Associate Editor of IEEE Transactions on Evolutionary Computation. He was the coordinator of the successful 2M euro EU-funded project SAGE which brought together the theory of evolutionary computation and population genetics.

 
 
 
 

This global health crisis is a unique challenge that has impacted many members of the IEEE family. These are difficult times, but we will get through them by working together. Thank you for your support of our shared mission to advance technology for humanity.
 
 
 
 

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