Call for Participation: AIDA Short Course on Deep Learning, 13 July 2025, AUTH, Thessaloniki, Greece with hybrid (local/remote) participation.

June 3rd, 2025 Daniela Lopez de Luise
Dear AI, CS/CSE, or ECE/EE student, scientist, engineer, professional,  AI enthusiast,

 

the International AI Doctoral Academy (AIDA) is excited to invite you to register and attend the upcoming hybrid (local/remote)

“Short Course on Deep Learning” by Prof. Ioannis Pitas (Aristotle University of Thessaloniki) which will take place in Aristotle University of Thessaloniki (AUTH), Greece, 13th July 2025.

This pre-symposium short course provides essential educational background for the AIDA AICET2025 Symposium and Summer School on “AI/ML Cutting Edge Trends” (July 14-18, 2025). However, participation in this short course is independent – attendees are welcomed but are not required to enroll in the AIDA AICET2025 Symposium and summer school.

 

This short course offers a good overview to all current progress in Deep Learning. It is ideal for persons (scientists, engineers, students, AI enthusiasts) interested in AI upskilling or reskilling. The only background knowledge needed is Mathematics (Calculus, Linear Algebra, Probability Theory) that are included in any Science or Engineering Curriculum. Persons coming from other backgrounds, e.g., Medicine or Linguistics, can also benefit, if they have some mathematical knowledge. 

 

Lectures

  1. Introduction to Machine Learning
  2. Artificial Neural Networks. Perceptron
  3. Multilayer Perceptron. Backpropagation.
  4. Convolutional Neural Networks
  5. Attention and Transformers Networks
  6. Large Language Models
  7. Generative Adversarial Networks in Multimedia Creation
  8. Generative AI and Diffusion Models

 

 

Details

📅 Date and Time: July 13, 2025, 9:00 – 19:00 EEST.

📍 On-site: KEDEA Building, AUTH, Thessaloniki, Greece.
💻 Online: Zoom link will be provided in due time.
📜 Certificate of Attendance will be provided upon request.

 

 

🔗 Register to the Short Course on Deep Learning: https://icarus.csd.auth.gr/pre-symposium-introductory-short-course-on-deep-learning/

 

Also, you can register to the AIDA AICET2025 Symposium and Short course and check its scholarship options in: https://icarus.csd.auth.gr/aida-auth-ai-cutting-edge-trends-aicet2025-summer-symposium-and-school/

 

👥 Group Registration: Group registrations (comprising 5 registrants or more) can enjoy a 20% discount on the above registration fees (or even more in the case of a massive group registration).

More information on the various lectures, registration options, background needed and general conditions can be found on the event webpage.

In case of questions, you can contact the course manager Ms. Efi Patmanidou epatman@csd.auth.gr

 

 

We're excited to have you join us for this thrilling Deep Learning course in the stunning city of Thessaloniki!

 

Best regards,

 

Prof. Ioannis Pitas (AIDA chair, AUTH, AICET2025 chair)

 

Post scriptum: To stay current on AIDA, AI, or CV/ML matters, you may want to register in the CVML email list, following instructions in: https://lists.auth.gr/sympa/info/cvml

 

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SUMAC’25 @ACMMM’25: the 7th ACM International workshop on analySis, Understanding and proMotion of heritAge Contents

June 3rd, 2025 Daniela Lopez de Luise
Call for Papers
SUMAC 2025
7th ACM International workshop on analySis, Understanding and proMotion of heritAge Contents
Advances in machine learning, signal processing, multimodal techniques and human-machine interaction
27 – 31 Oct, 2025
Dublin, Ireland
In conjunction with ACM Multimedia 2025
Main conference: https://acmmm2025.org/ 
 
*** Aims and scope
The ambition of SUMAC is to bring together researchers and practitioners from different disciplines to share ideas and methods on current trends in the analysis, understanding and promotion of heritage contents. These challenges are reflected in the corresponding sub- fields of machine learning, signal processing, multi-modal techniques and human-machine interaction. We welcome research contributions for the following (but not limited to) topics:
  • Information retrieval for multimedia heritage
  • Automated archaeology and heritage data processing
  • NLP and knowledge graphs
  • Multi-modal deep learning, generative modeling
  • Time series analysis for heritage data
  • Heritage visualization, virtualization and narratives
  • Smart digitization and reconstruction of heritage data
  • Open heritage data and bench-marking
The scope of targeted applications is extensive and includes:
  • Analysis, archaeometry of artifacts
  • Diagnosis and monitoring for restoration and preventive conservation
  • Geosciences / Geomatics for cultural heritage
  • Inclusive education
  • Smart and sustainable tourism
  • Urban planning
  • Digital Twins
*** Important dates (AoE)
  • Paper submission: July 11, 2025
  • Author acceptance notification: August 1, 2025
  • Camera-Ready: August 11, 2025
  • Workshop date: TBA (October 27 or 28, 2025)
*** Keynote speakers
  • Johan Oomen (Research Director, Netherlands Institute for Sound & Vision, The Netherlands): talk “TransMIXR : ignite the immersive media sector by enabling new narrative visions for cultural heritage”.
  • Diego Jiménez Badillo (Profesor Investigador, Instituto Nacional de Antropología e Historia, Mexico): talk “The analysis of cultural heritage in the age of Artificial Intelligence – application to archaeology and cultural heritage conservation”.
*** Special Highlights
Best Paper Award. Following tradition, SUMAC 2025 will also be awarding a best paper award, accompanied with a certificate and a trophy.
*** 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 (full paper) as well as work in progress (short paper). Two submission formats are accepted: a) 4 pages plus 1-page reference (short paper); or b) 8 pages plus up to 2-page reference (full paper). They must be encoded as PDF using the ACM Article Template of the main conference ACM Multimedia 2025, see https://acmmm2025.org/information-for-authors/. 
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. As for the main conference ACM MM, the workshop papers will be published in the ACM Digital Library.
*** Organizers
Valerie Gouet-Brunet (LaSTIG Lab / IGN-ENSG / Gustave Eiffel University, France)
Edgar Roman-Rangel (ITAM, Mexico)
Li Weng (Zhejiang Financial College, China)
Looking forward to hearing from you at SUMAC!
The workshop organizers

2025 4th International Workshop on Fine Art Pattern Extraction and Recognition – FAPER within ICIAP 2025

June 3rd, 2025 Daniela Lopez de Luise
2025 Second workshop on Explainable Artificial Intelligence for the medical domain – EXPLIMED
within the 28TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2025)

25-30 OCTOBER 2025 Bologna (Italy)
https://sites.google.com/view/explimed-2025/home-page
=============================================================================

AI has the potential to revolutionize medical care, but there are concerns about fairness and transparency. Explainable AI (XAI) is necessary to enhance transparency, accountability, and trustworthiness in medical AI systems. XAI provides understandable insights into AI-powered clinical decision-making, enabling healthcare professionals to trust recommendations and empowering patients to participate actively in their healthcare decisions. By addressing ethical concerns related to biased or discriminatory outcomes, XAI ensures fair and equitable healthcare practices. Finally, XAI aids in the validation process, offering insights into model predictions and facilitating the integration of AI technologies into clinical workflows.
This workshop aims to explore and exhibit research, methodologies, and case studies that focus on the integration of Explainable Artificial Intelligence (XAI) in the medical domain. It will provide a platform for researchers, practitioners, and policymakers to share their insights and advancements in XAI. The purpose is to improve transparency and trust in medical AI systems. The workshop aims to highlight the importance of XAI in medical decision-making, share innovative approaches and technologies that enhance interpretability in medical AI, and discuss regulatory implications and compliance strategies for incorporating XAI in healthcare AI applications.
Possible topics related to application in the healthcare domain include (but are not limited to):

– eXplainable Artificial Intelligence
– Post-hoc methods for explainability
– Ante-hoc methods for explainability
– Rule-based XAI systems
– Uncertainty modeling
– XAI methods for neuroimaging and neural signals
– Case-based explanations for AI systems
– Fuzzy systems for explainability
– Interpreting and explaining neural networks
– Model-specific vs model-agnostic methods
– Transparent and explainable learning methods
– Interpretable representational learning
– Causal inference and explanations
– Bayesian modeling for interpretability

**** IMPORTANT DATES ****

– Abstract submission deadline: May 10, 2025
– Paper submission deadline: May 21, 2025
– Notification of acceptance: July 21 2025
– Final paper submission: September 12, 2025
– Early registration deadline: TBA
– Workshop date:  25-26 October, 2025

**** SUBMISSIONS ****

Please ensure submissions follow the CEUR style guidelines, utilizing a one-column layout. Accepted paper formats include regular papers (10-20 pages) and short papers (5-9 pages) such as work-in-progress or position papers. Note: Both formats, if accepted, will be part of the workshop proceedings and must be written in English. Papers should be submitted in PDF format through the submission system (https://sites.google.com/view/explimed-2025/authors-guidelines/submissions). We encourage authors to use the LaTeX template and to include ORCIDs in their submissions. 
The workshop will be held in person. Each accepted paper will be assigned either an oral or a poster presentation. In case of a high number of submissions, some papers may be allocated as posters instead of oral presentations.

**** PUBLICATIONS ****
All papers submitted to the EXPLIMED workshop will undergo a double-blind review by independent reviewers. They will be published in the CEUR Workshop Proceedings under a CC-BY 4.0 license (http://ceur-ws.org/) upon acceptance. CEUR-WS proceedings are typically indexed in Scopus.

**** REGISTRATION ****
Please refer to the conference website: https://ecai2025.org/

**** KEYNOTE SPEAKER****
Alberto Fernández Hilario, Full Professor of Computer Science and Artificial Intelligence, University of Granada

**** ORGANIZING COMMITTEE ****
– Gabriella Casalino, University of Bari, Italy
– Giovanna Castellano, University of Bari, Italy
– Katarzyna Kaczmarek-Majer, Polish Academy of Sciences, Poland
– Raffaele Scaringi, University of Bari, Italy
– Gianluca Zaza, University of Bari, Italy

**** CONTACTS ****
Any inquiries can be directed to gianluca.zaza@uniba.it and raffaele.scaringi@uniba.it

 
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Satellite Workshop “Real-Time Implementation and Lightweight GNNs for Conventional and Event- based Cameras “, (RT-GNNs 2025) at IEEE ICIP 2025

June 3rd, 2025 Daniela Lopez de Luise
Call for Papers 

Website : https://sites.google.com/view/rt-gnns-2025/accueil

Description of Topic

Object classification and detection from a video stream captured by conventional cameras or event-based cameras is a fundamental step in applications such as visual surveillance of human activities, observation of animals and insect behaviors   human-machine interaction and all kinds of advanced mobile robotics perceptions systems. A large number of graph neural networks applied for detection and classification of moving objects have been published outperforming conventional deep learning approaches. Many scientific efforts have been reported in the literature to improve their application in a more progressive way in applications where challenges are becoming more complex.  But no algorithm is able to simultaneously address all the key challenges that are present in videos during long sequences as in the real cases.

However, the top background subtraction methods currently compared in CDnet 2014 are based on deep convolutional neural networks. But, their main drawbacks are computational and memory requirements, and also supervised aspects requiring labeling of a large amount of data. In addition, their performance decreases significantly in the presence of unseen videos. Thus, the current top algorithms are not practicable in real applications despite high performance regarding moving object detection.

In recent years, GNNs have also been increasingly used in object detection, object tracking, and mobile robot navigation. Their ability to model spatial and temporal dependencies makes them well-suited for these applications, especially in dynamic environments, where relationships between objects and scene elements must be continuously updated. However, real-time deployment of GNN-based solutions remains a challenge, as they often require significant computational resources, limiting their practicality in embedded and resource-constrained environments. Recently, only a few works have addressed real-time and lightweight GNN algorithms.

Hence, the goals of this workshop are thus three-fold:

1) Designing lightweight and practicable GNN algorithm that handles low- and high-level computer vision applications using conventional or event-based cameras;

2) proposing new algorithms that can fulfil the requirements of real-time applications, 

3) proposing robust and interpretable graph learning to handle the key challenges in these applications.

 

Papers are solicited to address deep learning methods to be applied in image and video processing, including but not limited to the following:

Graph Signal Processing for Computer Vision

Graph Machine Learning for Computer Vision

Transductive/Inductive Graph Neural Networks (GNNs)

GNNs Architectures

Zero-shot Learning

 Ensemble learning-based methods

Meta-knowledge Learning methods

RGB-D cameras

Event–based cameras

Hardware Architectures for Graph Processing

 

Main Organizers

Thierry Bouwmans, Associate Professor (HDR), Laboratoire MIA, La Rochelle Université, France.

Tomasz Kryjak, Assistant Professor, Embedded Vision Systems Group, Computer Vision Laboratory, AGH University of Krakow, Poland

Mohamed S. Shehata, Associate Professor, UBC Okanagan, Canada.

Ananda S. Chowdhury, Professor, Jadavpur University, India.

Badri N. Subudhi, Associate Professor, Indian Institute of Technology Jammu, India.

 

Important Dates

Workshop Paper Submission Deadline: 4 June 2025

Workshop Paper Acceptance Notification:  2 July 2025

Workshop Final Paper Submission Deadline: 9 July 2025

Workshop Author Registration Deadline : 16 July 2025

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Open sourcing the Neuro-SAN multiagent software

June 3rd, 2025 Daniela Lopez de Luise
Cognizant AI Lab (CAIL) recently open sourced the NeuroAI Multiagent Accelerator (Neuro-SAN) software for researchers. This software allows you to rapidly build coordinated multiagent systems consisting of multiple LLMs and other AI agents, and includes tools for visualization and performance analysis. See
   https://medium.com/@evolutionmlmail/neuro-san-is-all-you-need-0925aa7ae3d6
for a description, demos, and the repo. And if you are interested, we’d be happy give a demo e.g. at IEEE CEC, ICML, IJCNN, ITU AI for Good, GECCO, CogSci, or IJCAI.

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