Special Issue “Deepfakes, Fake News and Multimedia Manipulation from Generation to Detection”

Special Issue Information (Journal of Imaging)

Dear Colleagues,

Machine-learning-based techniques are being utilized to generate hyper-realistic manipulated facial multimedia content, known as DeepFakes. While such technologies have positive potentials for use in entertainment applications, the malevolent use of this technology can harm citizens and the society as a whole by facilitating the construction of indecent content, the spread of fake news to subvert elections or undermine politics, bullying, and the amelioration of social engineering to perpetrate financial fraud. In fact, it has been shown that manipulated facial multimedia content can not only deceive humans but also automated face-recognition-based biometric systems. The advent of advanced hardware, powerful smart devices, user-friendly apps (e.g., FaceApp and ZAO), and open-source ML codes (e.g., Generative Adversarial Networks) have enabled even non-experts to effortlessly create manipulated facial multimedia contents. In principle, face manipulation involves swapping two faces, modifying facial attributes (e.g., age and gender), morphing two different faces into one face, adding imperceptible perturbations (i.e., adversarial examples), synthetically generating faces, or animating/recreating facial expressions in face images/videos.

 Topics of interest of this Special Issue include, but are not limited to:

  • The generation of DeepFakes, face morphing, manipulation and adversarial attacks;
  • The generation of synthetic faces using ML/AI techniques, e.g., GANs;
  • The detection of DeepFakes, face morphing, manipulation and adversarial attacks, including generalizable systems;
  • The generation and detection of audio DeepFakes;
  • Novel datasets and experimental protocols to facilitate research in DeepFakes and face manipulations;
  • The formulation and extraction of DeepFake devices, platforms and software/app fingerprints;
  • Face recognition systems (and humans) against DeepFakes, face morphing, manipulation and adversarial attacks, including their vulnerabilities to digital face manipulations;
  • DeepFakes in the courtroom and on copyright law.

Deadline for manuscript submissions: 20 December 2022 (https://www.mdpi.com/journal/jimaging/special_issues/SI4UR5O9U9)


Keywords

  • DeepFakes
  • digital face manipulations
  • digital forensics
  • fake news
  • multimedia manipulations
  • generative AI
  • security and privacy
  • information authenticity
  • face morphing attack
  • biometrics

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Thank you.

Kind Regards,

MMM2023 – Call for Papers

Call for Papers for the International Conference on MultiMedia Modeling — MMM 2023, January 9-12, 2023 in Bergen, Norway



Deadline: September 2, 2022

MMM is a leading international conference for researchers and industry practitioners for sharing new ideas, original research results and practical development experiences from all MMM related areas. The conference calls for research papers reporting original investigation results and demonstrations reporting novel and compelling applications. Special sessions, Brave New Ideas session, keynote lectures, and the Video Browser Showdown will also contribute to a high-quality program.

Conference Website: http://mmm2023.no    

MMM 2023 hosts four special sessions: https://www.mmm2023.no/call-for-submissions/calls-for-special-session-papers 

  • MDRE: Multimedia Datasets for Repeatable Experimentation
  • MACHU: Multimedia Analytics for Contextual Human Understanding
  • ICDAR: Intelligent Cross-Data Analysis and Retrieval
  • SNL: Sport and Nutrition Lifelogging

MMM 2023 also hosts the following two workshops:
https://www.mmm2023.no/call-for-submissions/calls-for-workshop-papers

  • Research2biz: From Research To Prototype
  • URA: Second International Workshop on Understanding Reading Activities

Finally, MMM 2023 also hosts the Video Browser Showdown (VBS): https://videobrowsershowdown.org 

Submission Deadlines

  • All submissions to the main conference track and Special Sessions: September 2, 2022
  • Workshop deadlines and the VBS deadline are separately defined by the workshop and VBS organisers
On behalf of the MMM 2023 organisers

Third Call for Papers of AICI 2023: deadline extended to August 31


 

Hanoi, 16 August 2022

 

Dear Friends and colleagues

 

If you are interested in submitting a paper for AICI 2023, pls. consider that

the Paper Submission Deadline is extended to August 31, 2022.

 

FOURTH CALL FOR PAPERS

The Fourth International Conference on Artificial Intelligence and Computational Intelligence 

(AICI 2023)

Hanoi, Vietnam,

January 13-14,  2023

 

Organized by Thang Long University together with VFSS

Sponsored by International Fuzzy Systems Association (IFSA)

(by hybrid modes: direct mode and online mode)

 

Venue: Thang Long University, Nghiem Xuan Yem Rd., Hoang Mai District, Hanoi, Vietnam

 (https://thanglong.edu.vn/)

 

This conference aims at bringing together researchers in Artificial Intelligence and Computational Intelligence and related topics for an opportunity to present and discuss theoretical and applied research problems as well as to foster research collaborations.

 

Themes: Deep Learning and Other Soft Computing Techniques: Biomedical and Related Applications

 

Topics of interest include but are not limited to, the following:

Artificial Intelligence 

AI Algorithms

Artificial Intelligence tools & Applications

Automatic Control

Knowledge-based Systems

Robotics

……

Computational Intelligence 

Fuzzy Systems

Neural Networks

Machine learning

Deep learning

Big data

……

 

Website: https://aici2023.thanglong.edu.vn 

 

Publications:

Accepted papers for presentation at AICI 2023 will be published in the Springer book series “Studies in Systems, Decision, and Control” indexed by Scopus, DBLP, WTI Frankfurt eG, zbMATH, SCImago.

 

 

Registration Fees:

For participants who choose online mode:

Authors: 200 US$

Vietnamese Authors: 3.000.000 VNĐ (3 triệu VNĐ)

Participants: Free

For participants who choose a direct  mode:

Authors: 400 US$

Student Authors: 300 US$

Vietnamese Authors: 4.000.000 VNĐ (4 triệu VNĐ)

 

Participants:

100 US$ for foreign participants

500.000 VNĐ (0,5 triệu VNĐ) for Vietnamese participants

 

Important dates:  

– Paper Submission Deadline: (August 15, 2022)  is extended to August 31, 2022

– Notification of acceptance:  October 1, 2022 (with instructions for submitting the final manuscript and Copyright Agreement form of Springer).

– Final version submission deadline: October 31, 2022

– Conference: 13-14 January 2023

– We organize One day Trang An tour: 15 January 2023 (https://hanoiexploretravel.com/ninh-binh-itinerary/trang-an-day-tour-from-hanoi)

 

How to submit

We invite scientific publications up to 12 pages, which may be submitted in PDF via the Easychair system below: https://easychair.org/conferences/?conf=aici2023.

 

General Chair:

Phan Huy Phu (Thang Long University, Vietnam)

 

Scientific Committee Chairs:

Hung T. Nguyen (NMSU, USA; ChiangMai Univ., Thailand)

Vladik Kreinovich (UTEP, USA)

Nguyen Hoang Phuong (Thang Long University, Vietnam)

 

Organizing Committee Chairs:

Cao Kim Anh

Nguyen Hoang Phuong

 

Contact person : Nguyen Hoang Phuong,

                             Informatics Division, Thang Long University, Vietnam

                             email: phuongnh@thanglong.edu.vn

                             (email: nhphuong2008@gmail.com ; Mob. (+84) 904 128 118)

 

 

We are looking forward to seeing you (direct or online) in AICI 2023 in January 2023 in Hanoi.

 

Warmest regards.

 

Assoc. Prof. Dr. Nguyen Hoang Phuong, co-organizer of AICI 2023,

Artificial Intelligence Division, Informatics Faculty, Thang Long University, Vietnam

 

DeepLearn 2022 Autumn: early registration August 15

     
 
 
7th INTERNATIONAL SCHOOL ON DEEP LEARNING
 
 
 
DeepLearn 2022 Autumn
 
 
 
Luleå, Sweden
 
 
 
October 17-21, 2022
 
 
 
 
 
 
*****************
 
 
 
Co-organized by:
 
 
 
Luleå University of Technology
 
EISLAB Machine Learning
 
 
 
Institute for Research Development, Training and Advice – IRDTA
 
Brussels/London
 
 
 
******************************************************************
 
 
 
Early registration: August 15, 2022
 
 
 
******************************************************************
 
 
 
SCOPE:
 
 
 
DeepLearn 2022 Autumn will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães and Las Palmas de Gran Canaria.
 
 
 
Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, health informatics, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, biometrics, communications, climate sciences, bioinformatics, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience.
 
 
 
Most deep learning subareas will be displayed, and main challenges identified through 21 four-hour and a half courses and 2 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely.
 
 
 
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles.
 
 
 
ADDRESSED TO:
 
 
 
Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2022 Autumn is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators.
 
 
 
VENUE:
 
 
 
DeepLearn 2022 Autumn will take place in Luleå, on the coast of northern Sweden, hosting a large steel industry and the northernmost university in the country. The venue will be:
 
 
 
Luleå University of Technology
 
 
 
 
 
 
STRUCTURE:
 
 
 
3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
 
 
 
Full live online participation will be possible. However, the organizers highlight the importance of face to face interaction and networking in this kind of research training event.
 
 
 
KEYNOTE SPEAKERS:
 
 
 
Tommaso Dorigo (Italian National Institute for Nuclear Physics), Deep-Learning-Optimized Design of Experiments: Challenges and Opportunities
 
 
 
Elaine O. Nsoesie (Boston University), AI and Health Equity
 
 
 
PROFESSORS AND COURSES:
 
 
 
Sean Benson (Netherlands Cancer Institute), [intermediate] Deep Learning for a Better Understanding of Cancer
 
 
 
Thomas Breuel (Nvidia), [intermediate/advanced] Large Scale Deep Learning and Self-Supervision in Vision and NLP
 
 
 
Hao Chen (Hong Kong University of Science and Technology), [introductory/intermediate] Label-Efficient Deep Learning for Medical Image Analysis
 
 
 
Jianlin Cheng (University of Missouri), [introductory/intermediate] Deep Learning for Bioinformatics
 
 
 
Nadya Chernyavskaya (European Organization for Nuclear Research), [intermediate] Graph Networks for Scientific Applications with Examples from Particle Physics
 
 
 
Sébastien Fabbro (University of Victoria), [introductory/intermediate] Learning with Astronomical Data
 
 
 
Efstratios Gavves (University of Amsterdam), [advanced] Advanced Deep Learning
 
 
 
Quanquan Gu (University of California Los Angeles), [intermediate/advanced] Benign Overfitting in Machine Learning: From Linear Models to Neural Networks
 
 
 
Jiawei Han (University of Illinois Urbana-Champaign), [advanced] Text Mining and Deep Learning: Exploring the Power of Pretrained Language Models
 
 
 
Awni Hannun (Zoom), [intermediate] An Introduction to Weighted Finite-State Automata in Machine Learning [virtual]
 
 
 
Tin Kam Ho (IBM Thomas J. Watson Research Center), [introductory/intermediate] Deep Learning Applications in Natural Language Understanding
 
 
 
Timothy Hospedales (University of Edinburgh), [intermediate/advanced] Deep Meta-Learning
 
 
 
Shih-Chieh Hsu (University of Washington), [intermediate/advanced] Real-Time Artificial Intelligence for Science and Engineering
 
 
 
Andrew Laine (Columbia University), [introductory/intermediate] Applications of AI in Medical Imaging
 
 
 
Tatiana Likhomanenko (Apple), [intermediate/advanced] Self-, Weakly-, Semi-Supervised Learning in Speech Recognition
 
 
 
Peter Richtárik (King Abdullah University of Science and Technology), [intermediate/advanced] Introduction to Federated Learning
 
 
 
Othmane Rifki (Spectrum Labs), [introductory/advanced] Speech and Language Processing in Modern Applications
 
 
 
Mayank Vatsa (Indian Institute of Technology Jodhpur), [introductory/intermediate] Small Sample Size Deep Learning
 
 
 
Yao Wang (New York University), [introductory/intermediate] Deep Learning for Computer Vision
 
 
 
Zichen Wang (Amazon Web Services), [introductory/intermediate] Graph Machine Learning for Healthcare and Life Sciences
 
 
 
Alper Yilmaz (Ohio State University), [introductory/intermediate] Deep Learning and Deep Reinforcement Learning for Geospatial Localization
 
 
 
OPEN SESSION:
 
 
 
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david@irdta.eu by October 9, 2022.
 
 
 
INDUSTRIAL SESSION:
 
 
 
A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david@irdta.eu by October 9, 2022.
 
 
 
EMPLOYER SESSION:
 
 
 
Organizations searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the organization and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david@irdta.eu by October 9, 2022.
 
 
 
ORGANIZING COMMITTEE:
 
 
 
Nosheen Abid (Luleå)
 
Sana Sabah Al-Azzawi (Luleå)
 
Lama Alkhaled (Luleå)
 
Prakash Chandra Chhipa (Luleå)
 
Saleha Javed (Luleå)
 
Marcus Liwicki (Luleå, local chair)
 
Carlos Martín-Vide (Tarragona, program chair)
 
Hamam Mokayed (Luleå)
 
Sara Morales (Brussels)
 
Mia Oldenburg (Luleå)
 
Maryam Pahlavan (Luleå)
 
David Silva (London, organization chair)
 
Richa Upadhyay (Luleå)
 
 
 
REGISTRATION:
 
 
 
It has to be done at
 
 
 
 
 
 
The selection of 8 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish.
 
 
 
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event.
 
 
 
FEES:
 
 
 
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participants are the same.
 
 
 
ACCOMMODATION:
 
 
 
Accommodation suggestions are available at
 
 
 
 
 
 
CERTIFICATE:
 
 
 
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
 
 
 
QUESTIONS AND FURTHER INFORMATION:
 
 
 
 
 
 
ACKNOWLEDGMENTS:
 
 
 
Luleå University of Technology, EISLAB Machine Learning
 
 
 
Rovira i Virgili University
 
 
 
Institute for Research Development, Training and Advice – IRDTA, Brussels/London
      

DeepLearn 2022 Autumn: early registration August 15

     
 
 
7th INTERNATIONAL SCHOOL ON DEEP LEARNING
 
 
 
DeepLearn 2022 Autumn
 
 
 
Luleå, Sweden
 
 
 
October 17-21, 2022
 
 
 
 
 
 
*****************
 
 
 
Co-organized by:
 
 
 
Luleå University of Technology
 
EISLAB Machine Learning
 
 
 
Institute for Research Development, Training and Advice – IRDTA
 
Brussels/London
 
 
 
******************************************************************
 
 
 
Early registration: August 15, 2022
 
 
 
******************************************************************
 
 
 
SCOPE:
 
 
 
DeepLearn 2022 Autumn will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães and Las Palmas de Gran Canaria.
 
 
 
Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, health informatics, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, biometrics, communications, climate sciences, bioinformatics, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience.
 
 
 
Most deep learning subareas will be displayed, and main challenges identified through 21 four-hour and a half courses and 2 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely.
 
 
 
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles.
 
 
 
ADDRESSED TO:
 
 
 
Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2022 Autumn is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators.
 
 
 
VENUE:
 
 
 
DeepLearn 2022 Autumn will take place in Luleå, on the coast of northern Sweden, hosting a large steel industry and the northernmost university in the country. The venue will be:
 
 
 
Luleå University of Technology
 
 
 
 
 
 
STRUCTURE:
 
 
 
3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
 
 
 
Full live online participation will be possible. However, the organizers highlight the importance of face to face interaction and networking in this kind of research training event.
 
 
 
KEYNOTE SPEAKERS:
 
 
 
Tommaso Dorigo (Italian National Institute for Nuclear Physics), Deep-Learning-Optimized Design of Experiments: Challenges and Opportunities
 
 
 
Elaine O. Nsoesie (Boston University), AI and Health Equity
 
 
 
PROFESSORS AND COURSES:
 
 
 
Sean Benson (Netherlands Cancer Institute), [intermediate] Deep Learning for a Better Understanding of Cancer
 
 
 
Thomas Breuel (Nvidia), [intermediate/advanced] Large Scale Deep Learning and Self-Supervision in Vision and NLP
 
 
 
Hao Chen (Hong Kong University of Science and Technology), [introductory/intermediate] Label-Efficient Deep Learning for Medical Image Analysis
 
 
 
Jianlin Cheng (University of Missouri), [introductory/intermediate] Deep Learning for Bioinformatics
 
 
 
Nadya Chernyavskaya (European Organization for Nuclear Research), [intermediate] Graph Networks for Scientific Applications with Examples from Particle Physics
 
 
 
Sébastien Fabbro (University of Victoria), [introductory/intermediate] Learning with Astronomical Data
 
 
 
Efstratios Gavves (University of Amsterdam), [advanced] Advanced Deep Learning
 
 
 
Quanquan Gu (University of California Los Angeles), [intermediate/advanced] Benign Overfitting in Machine Learning: From Linear Models to Neural Networks
 
 
 
Jiawei Han (University of Illinois Urbana-Champaign), [advanced] Text Mining and Deep Learning: Exploring the Power of Pretrained Language Models
 
 
 
Awni Hannun (Zoom), [intermediate] An Introduction to Weighted Finite-State Automata in Machine Learning [virtual]
 
 
 
Tin Kam Ho (IBM Thomas J. Watson Research Center), [introductory/intermediate] Deep Learning Applications in Natural Language Understanding
 
 
 
Timothy Hospedales (University of Edinburgh), [intermediate/advanced] Deep Meta-Learning
 
 
 
Shih-Chieh Hsu (University of Washington), [intermediate/advanced] Real-Time Artificial Intelligence for Science and Engineering
 
 
 
Andrew Laine (Columbia University), [introductory/intermediate] Applications of AI in Medical Imaging
 
 
 
Tatiana Likhomanenko (Apple), [intermediate/advanced] Self-, Weakly-, Semi-Supervised Learning in Speech Recognition
 
 
 
Peter Richtárik (King Abdullah University of Science and Technology), [intermediate/advanced] Introduction to Federated Learning
 
 
 
Othmane Rifki (Spectrum Labs), [introductory/advanced] Speech and Language Processing in Modern Applications
 
 
 
Mayank Vatsa (Indian Institute of Technology Jodhpur), [introductory/intermediate] Small Sample Size Deep Learning
 
 
 
Yao Wang (New York University), [introductory/intermediate] Deep Learning for Computer Vision
 
 
 
Zichen Wang (Amazon Web Services), [introductory/intermediate] Graph Machine Learning for Healthcare and Life Sciences
 
 
 
Alper Yilmaz (Ohio State University), [introductory/intermediate] Deep Learning and Deep Reinforcement Learning for Geospatial Localization
 
 
 
OPEN SESSION:
 
 
 
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david@irdta.eu by October 9, 2022.
 
 
 
INDUSTRIAL SESSION:
 
 
 
A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david@irdta.eu by October 9, 2022.
 
 
 
EMPLOYER SESSION:
 
 
 
Organizations searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the organization and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david@irdta.eu by October 9, 2022.
 
 
 
ORGANIZING COMMITTEE:
 
 
 
Nosheen Abid (Luleå)
 
Sana Sabah Al-Azzawi (Luleå)
 
Lama Alkhaled (Luleå)
 
Prakash Chandra Chhipa (Luleå)
 
Saleha Javed (Luleå)
 
Marcus Liwicki (Luleå, local chair)
 
Carlos Martín-Vide (Tarragona, program chair)
 
Hamam Mokayed (Luleå)
 
Sara Morales (Brussels)
 
Mia Oldenburg (Luleå)
 
Maryam Pahlavan (Luleå)
 
David Silva (London, organization chair)
 
Richa Upadhyay (Luleå)
 
 
 
REGISTRATION:
 
 
 
It has to be done at
 
 
 
 
 
 
The selection of 8 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish.
 
 
 
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event.
 
 
 
FEES:
 
 
 
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participants are the same.
 
 
 
ACCOMMODATION:
 
 
 
Accommodation suggestions are available at
 
 
 
 
 
 
CERTIFICATE:
 
 
 
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
 
 
 
QUESTIONS AND FURTHER INFORMATION:
 
 
 
 
 
 
ACKNOWLEDGMENTS:
 
 
 
Luleå University of Technology, EISLAB Machine Learning
 
 
 
Rovira i Virgili University
 
 
 
Institute for Research Development, Training and Advice – IRDTA, Brussels/London
      
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