The IC MarkTech – Marketing and Technologies will take place at the University of La Laguna, Tenerife, Spain, on December 2 – 4, 2021. The submission deadline was extended to September 22nd and the articles presented will be published in the Smart Innovation, Systems and Technologies series (Springer Nature; indexed in Scopus among others), besides the possibility of the publication of extended versions of the best papers in academic journals (EJMBE, CogBM, IM, DTA, among others). You may find the detailed call for papers here.

Scope
ICMarkTech'21 – The 2021 International Conference on Marketing and Technologies (www.icmarktech.org), which will be held at the University of La Laguna, in the island of Tenerife in Spain, between 2 and 4 December 2021, is an international forum for researchers and professionals to present and discuss the latest innovations, trends, results, experiences, and concerns in the various fields of Marketing and Technologies related to it.
We are pleased to invite you to submit your articles to ICMarkTech'21. All submitted articles will be reviewed based on their relevance, originality, importance, and clarity.

Topics
Papers submitted should relate to one or more of the main themes proposed for the Conference:

1. Artificial Intelligence Applied in Marketing
2. Virtual and Augmented Reality in Marketing
3. Business Intelligence Databases and Marketing
4. Data Mining and Big Data – Marketing Data Science
5. Web Marketing, e-commerce, and v-commerce
6. Social Media and Networking
7. Omnichannel and Marketing Communication
8. Marketing, Geomarketing, and IoT
9. Marketing Automation and Marketing Inbound
10. Machine Learning Applied to Marketing
11. Customer Data Management and CRM
12. Neuromarketing Technologies
13. Mobile Marketing and Wearable Technologies
14. Gamification Technologies to Marketing
15. Blockchain Applied to Marketing
16. Technologies Applied to Tourism Marketing

Submissions and Decisions
Submitted papers must comply with the format of Smart Innovation, Systems and Technologies (see Instructions for Authors at Springer Website), be written in English, must not have been published before, not be under review for any other conference or publication and not include any information leading to the authors’ identification. Therefore, the authors’ names, affiliations, and bibliographic references should not be included in the version for evaluation by the Scientific Committee. This information should only be included in the camera-ready version, saved in Word or Latex format, and also in PDF format. These files must be accompanied by the Consent to Publish form filled out, in a ZIP file, and uploaded to the conference management system.
All papers will be subjected to a “double-blind review” by at least two members of the Scientific Committee.
Based on Scientific Committee evaluation, a paper can be rejected or accepted by the Conference Chairs. In the latter case, it can be accepted as the type originally submitted or as another type.
The authors of accepted papers will have 15 minutes to present their work in a Conference Work Session; approximately 5 minutes of discussion will follow each presentation.

Publication and Indexing
To ensure that a full paper, poster paper, or company paper is published, at least one of the authors must be fully registered by the 15th of October 2021, and the paper must comply with the suggested layout and page limit. Additionally, all recommended changes must be addressed by the authors before they submit the camera-ready version.
No more than one paper per registration will be published. An extra fee must be paid for the publication of additional papers, with a maximum of one additional paper per registration. One registration permits only the participation of one author in the conference.
Papers will be published in Proceedings by Springer, in the SIST series. Company papers will not be published, just presented at the conference.
Published full papers will be submitted for indexation by ISI, EI-Compendex, SCOPUS, DBLP, and Google Scholar, among others, and will be available in the SpringerLink Digital Library.

Important Dates
Paper Submission: September 22nd, 2021
Notification of Acceptance: September 30th, 2021
Payment of Registration, to ensure the inclusion of an accepted paper in the conference proceedings: October 15th, 2021
Camera-ready Submission: October 15th, 2021

Kind regards,

The Coordinating Committee

Dear Machine Learning and Deep Neural Networks engineers, scientists and enthusiasts,

 

you are welcomed to register in the  CVML Short e-course on ‘Deep Learning and Computer Vision’,  6-7^th October 2021: http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-vision-for-autonomous-systems-2021/

 

It will take place as a two-day e-course (due to COVID-19 circumstances), hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece, providing a series of live lectures delivered through a tele-education platform (Zoom). They will be complemented with on-line video recorded lectures and lecture pdfs, to facilitate international participants having time difference issues and to enable you to study at own pace.  You can also self-assess your knowledge, by filling appropriate questionnaires (one per lecture). You will be provided programming to improve your programming skills. You will also have accesses to tutorial exercises to better your theoretical understanding of selected CVML topics.

This 6^th edition of this course is part of the very successful CVML short course series that took place in the last four years.

 

Course description ‘Deep Learning and Computer Vision’

The short e-course consists of 16 1-hour live lectures organized in two Parts (1 Part per day):

Part A lectures (8 hours) provide an in-depth presentation to autonomous systems imaging and the relevant architectures as well as a solid background on the necessary topics of computer vision (Image acquisition, camera geometry, Stereo and Multiview imaging, Mapping and Localization) and machine learning (Introduction to neural networks, Perceptron, backpropagation, Deep neural networks, Convolutional NNs).

Part B lectures (8 hours) provide in-depth views of the various topics encountered in autonomous systems perception, ranging from vehicle localization and mapping, to Neural SLAM, target detection and tracking. Part B also contains application-oriented lectures on autonomous drones, cars and marine vessels, e.g., drone mission planning for cinematography and related applications (marine surveillance, infrastructure/building inspection, car vision).

 

Course lectures

Part A: (first day, 8 lectures)

1. Introduction to autonomous systems imaging
2. Digital Image and Videos
3. Camera geometry
4. Stereo and Multiview imaging
5. Introduction to Artificial Neural Networks. Perceptron
6. Multilayer perceptron. Backpropagation
7. Deep neural networks. Convolutional NNs
8. Introduction to multiple drone imaging

Part B: (second day, 8 lectures)

1. Simultaneous Localization and Mapping
2. Neural Slam
3. Deep Object Detection
4. 2D Visual Object Tracking
5. Drone mission planning and control
6. Introduction to car vision
7. Introduction to autonomous marine vehicles
8. CVML Software Development Tools

 

 

You can use the following link for course registration:

http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-vision-for-autonomous-systems-2021/

 

Lecture topics, sample lecture ppts and videos, self-assessment questionnaires, programming exercises and tutorial exercises can be found therein.

For questions, please contact: Ioanna Koroni <koroniioanna@csd.auth.gr>

 

The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow and IEEE distinguished speaker.  He is the coordinator of the EC funded International AI Doctoral Academy (AIDA), that is co-sponsored by all 5 European AI R&D flagship projects (H2020 ICT48). He was initiator and first Chair of the IEEE SPS Autonomous Systems Initiative. He is Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece. He was Coordinator of the European Horizon2020 R&D project Multidrone. He is ranked 249-top Computer Science and Electronics scientist internationally by Guide2research (2018). He has 33800+ citations to his work and h-index 86+.

 

AUTH is ranked 153/182 internationally in Computer Science/Engineering, respectively, in USNews ranking.

 

Relevant links:

1) Prof. I. Pitas:

https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el

2) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/

3) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/

4) International AI Doctoral Academy (AIDA): http://www.i-aida.org/

5) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/

6) AIIA Lab: https://aiia.csd.auth.gr/

 

Sincerely yours

Prof. I. Pitas

Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab)

Aristotle University of Thessaloniki, Greece