Dear Machine Learning, Computer Vision and Autonomous Systems engineers, scientists and enthusiasts,

you are welcomed to register in the CVML Short course on Deep Learning and Computer Vision,  28-29^th August 2023:
https://icarus.csd.auth.gr/cvml-short-course-deep-learning-and-computer-vision-2023/  
with various Computer Vision and Deep Learning applications, e.g., for big visual data analysis, autonomous vehicles (drones, cars and marine vessels), digital media analysis, intelligent human-machine interaction,  anthropocentric (human-centered) computing, smart cities/buildings and assisted living, natural disaster management. 

It will take place at KEDEA Building, hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece.
The  course consists of 16 lectures, providing an in-depth presentation of many computer vision and deep learning hot topics, finding applications in big visual data analysis, autonomous vehicle vision, digital media analysis and human centered computing. There will be complemented with lecture pdfs 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 pointers to improve your skills.
You will also have access to tutorial exercises to better your theoretical understanding of selected CVML topics.
This 6^th edtion of this course is part of the very successful CVML short course series that has been taking place in the last four years.

Course description ‘Deep Learning and Computer Vision’

The short course consists of 16 live lectures organized in two Parts (1 Part per day):
Part A lectures (8 hours) provide an in-depth presentation of Deep Neural Networks, which are at the forefront of AI advances today, starting with an introduction to Machine Learning. Then the cornerstone DNN theory and technologies are presented.
Part B lectures (8 hours) provide an in-depth presentation of both 2D and 3D Computer Vision theory and its applications in the above-mentioned diverse domains.  3D Computer Vision starts with a detailed presentation of camera geometry, including camera calibration.
 
 
Course lectures
Part A (8 hours), Deep Neural Networks topic list

1. Multilayer perceptron. Backpropagation
2. Deep neural networks. Convolutional NNs 
3. Recurrent Neural Networks  
4. Attention and Transformers
5. Attention in Computer Vision
6. Generative Adversarial Networks  
7. Diffusion Models
8. Deep Reinforcement Learning models 

 
Part B (8 hours) 2D and 3D Computer Vision topic list

1. Camera geometry  
2. Stereo and Multiview imaging  
3. Structure from motion  
4. Object detection and tracking 
5. Region segmentation and pose estimation 
6. Human action recognition 

 
Though independent, the attendees of this short course will greatly benefit by attending the CVML Programming Short Course and Workshop on Deep Learning and Computer Vision 2022, that will take place between August 30 and September 1, 2023:
http://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-deep-learning-and-computer-vision-2023/
 
You can use the following link for course registration:
https://rc.auth.gr/product-list/single-product/125

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 is Coordinator of the European Horizon2022 R&D project TEMA and 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 35500+ 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) Horizon2022 EU funded R&D project TEMA:  https://tema-project.eu/

3) Horizon2022 EU funded R&D project AI4EUROPE:  https://www.ai4europe.eu/

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

5) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/
6) International AI Doctoral Academy (AIDA): http://www.i-aida.org/
7) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/
8) AIIA Lab: https://aiia.csd.auth.gr/
 
Sincerely yours
Prof. I. Pitas
Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab)
Chair of the International AI Doctoral Academy (AIDA)
Aristotle University of Thessaloniki, Greece
 
Post scriptum: To stay current on CVML matters, you may want to register in the CVML email list, following instructions in: https://lists.auth.gr/sympa/info/cvml

BigDat 2023 Summer

Las Palmas de Gran Canaria, Spain

July 17-21, 2023

https://bigdat.irdta.eu/2023su

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Co-organized by:

University of Las Palmas de Gran Canaria

Institute for Research Development, Training and Advice – IRDTA
Brussels/London

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Early registration: June 19, 2023

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FRAMEWORK:

BigDat 2023 Summer is part of a multi-event called Deep&Big 2023 consisting also of DeepLearn 2023 Summer. BigDat 2023 Summer participants will have the opportunity to attend lectures in the program of DeepLearn 2023 Summer as well if they are interested.

SCOPE:

BigDat 2023 Summer 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 big data. Previous events were held in Tarragona, Bilbao, Bari, Timisoara, Cambridge and Ancona.

Big data is a broad field covering a large spectrum of current exciting research and industrial innovation with an extraordinary potential for a huge impact on scientific discoveries, health, engineering, business models, and society itself. Renowned academics and industry pioneers will lecture and share their views with the audience.

Most big data subareas will be displayed, namely foundations, infrastructure, management, search and mining, analytics, security and privacy, as well as applications to biology and medicine, business, finance, transportation, online social networks, etc. Major challenges of analytics, management and storage of big data will be identified through 14 four-hour and a half courses, 1 keynote lecture and 1 round table, 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 employment 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, BigDat 2023 Summer 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:

BigDat 2023 Summer will take place in Las Palmas de Gran Canaria, on the Atlantic Ocean, with a mild climate throughout the year, sandy beaches and a renowned carnival. The venue will be:

Institución Ferial de Canarias
Avenida de la Feria, 1
35012 Las Palmas de Gran Canaria

https://www.infecar.es/

STRUCTURE:

2 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.

Also, if interested, participants will be able to attend courses developed in DeepLearn 2023 Summer, which will be held in parallel and at the same venue.

Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event.

KEYNOTE SPEAKER:

Sander Klous (University of Amsterdam), How to Audit an Analysis on a Federative Data Exchange

PROFESSORS AND COURSES:

Paolo Addesso (University of Salerno), [introductory/intermediate] Data Fusion for Remotely Sensed Data

Marcelo Bertalmío (Spanish National Research Council), [introductory] The Standard Model of Vision and Its Limitations: Implications for Imaging, Vision Science and Artificial Neural Networks

Gianluca Bontempi (Université Libre de Bruxelles), [intermediate/advanced] Big Data Analytics in Fraud Detection and Churn Prevention: from Prediction to Causal Inference

Altan Çakir (Istanbul Technical University), [introductory/intermediate] Introduction to Big Data with Apache Spark

Ian Fisk (Flatiron Institute), [introductory] Setting Up a Facility for Data Intensive Science Analysis

Ravi Kumar (Google), [intermediate/advanced] Differential Privacy

Wladek Minor (University of Virginia), [introductory/advanced] Big Data in Biomedical Sciences

José M.F. Moura (Carnegie Mellon University), [introductory/intermediate] Graph Signal Processing and Geometric Learning

Panos Pardalos (University of Florida), [intermediate/advanced] Data Analytics for Massive Networks

Ramesh Sharda (Oklahoma State University), [introductory/intermediate] Network-Based Health Analytics

Steven Skiena (Stony Brook University), [introductory/intermediate] Word and Graph Embeddings for Machine Learning

Mayte Suarez-Farinas (Icahn School of Medicine at Mount Sinai), [intermediate] Meta-Analysis Methods for High-Dimensional Data

Ana Trisovic (Harvard University), [introductory/advanced] Principles, Statistical and Computational Tools for Reproducible Data Science

Sebastián Ventura (University of Córdoba), [intermediate] Supervised Descriptive Pattern Mining

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 July 9, 2023.

INDUSTRIAL SESSION:

A session will be devoted to 10-minute demonstrations of practical applications of big data 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 July 9, 2023.

EMPLOYER SESSION:

Organizations searching for personnel well skilled in big data 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 July 9, 2023.

ORGANIZING COMMITTEE:

Aridane González González (Las Palmas de Gran Canaria)
Marisol Izquierdo (Las Palmas de Gran Canaria, local chair)
Carlos Martín-Vide (Tarragona, program chair)
Sara Morales (Brussels)
David Silva (London, organization chair)

REGISTRATION:

It has to be done at

https://bigdat.irdta.eu/2023su/registration/

The selection of 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, 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 as well as eventually courses in DeepLearn 2023 Summer.

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 participation are the same.

ACCOMMODATION:

Accommodation suggestions are available at

https://bigdat.irdta.eu/2023su/accommodation/

CERTIFICATE:

A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.

QUESTIONS AND FURTHER INFORMATION:

david@irdta.eu

ACKNOWLEDGMENTS:

Cabildo de Gran Canaria

Universidad de Las Palmas de Gran Canaria – Fundación Parque Científico Tecnológico

Universitat Rovira i Virgili

Institute for Research Development, Training and Advice – IRDTA, Brussels/London