Call for Papers & Talks | ContinualAI Unconference 2023

 

We are pleased to announce the Call for Papers (to be published in PMLR) and Call for Talks for the upcoming ContinualAI Unconference (CLAI Unconf). Organized by the non-profit research organization, ContinualAI, the conference seeks to accelerate inclusive and sustainable progress in our academic community through a unique, open-access, multi-timezone, 24-hour event which will be free to attend. The event will connect ideas beyond static datasets at the crossroads of machine learning, computational neuroscience, robotics, and more. Stay up to date by visiting our webpage: https://unconf.continualai.org 

 

Please note the following important dates:

– Virtual Conference Date: October 19, 2023

Call for Papers Deadline: July 21, 2023

Call for Talks Deadline: August 18, 2023

 

Different from traditional conferences, CLAI Unconf allows you to

1) Preregister your ideas with accepted papers published in PMLR Call for Papers)

2) Share an idea with the experts in the field with a 5 to 15 minute talk (Call for Talks)

 

We are currently inviting original contributions that delve into the dynamic aspects of AI, straying from the static train-test paradigm prevalent in much of the current AI research. The conference themes include, but are not limited to:

  • Navigating complex data collection systems
  • Understanding and describing continuous streams of data
  • Lifelong learning processes and generalization of knowledge beyond a specific target
  • Discovering new concepts in changing environments and handling partially observable information from potentially disparate data sources
  • Interdisciplinary perspectives on related topics
  • A more detailed account of the conference themes is available in our Call for Papers.

 

CLAI Unconf offers a unique experience with features such as:

  • Free for everyone
  • Easy accessibility through virtual, multi-timezone support
  • Contributed talks and pre-registration articles
  • Active roundtables encouraging participant interaction and discussions
  • Hands-on sessions promoting collaborative work and creativity
  • Mentoring Sessions

 

In addition, we offer an exciting pre-registration submission process to ensure scientific excellence (a more detailed account of pre-registration is provided in our Call for Papers). Researchers are invited to present well-articulated ideas and thoroughly outlined experimental protocols. These ideas will be evaluated and discussed during the conference, with follow-up findings published in CLAI Unconf's Proceedings of Machine Learning Research (PMLR).

 

We believe this conference provides a unique opportunity to exchange ideas and explore new concepts in the field of Artificial Intelligence. We look forward to receiving your submissions and meeting you at the un-conference! Please feel free to forward this advertisement along to your network.

 

Best regards,

 

James Seale Smith

Outreach Chair

ContinualAI Unconference Organizing Committee

 

 

Special Issue on “Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis” at MTAP

Call for Papers: Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis

https://www.springer.com/journal/11042/updates/24678968

Summary and Scope

Nowadays, Deep learning (DL) becomes an attractive research topic for many researchers from academia and industry communities. Indeed, DL algorithms have demonstrated their ability to train learning models for large-volume data as well as their performances compared to conventional machine learning algorithms. The DL approaches were studied and applied to resolve several complex problems in various research domains, such as computer vision, biometrics, brain-computer interfaces, robotics, and other fields. Several architectures of DL (e.g., supervised, unsupervised, reinforcement, and beyond) have been proposed in the literature as solutions for various research problems in data analysis related to detection, classification, recognition, prediction, decision-making, etc.

The special issue aims to solicit original research work covering novel algorithms, innovative methods, and meaningful applications based on the DL that can potentially lead to significant advances in biomedical data analysis.

The main topics include, but are not limited to, the following:

• DL for biomedical signal analysis and processing
• DL for medical image analysis and processing
• DL for diseases detection and diagnosis
• DL for pandemics detection and forecasting
• DL for biometrics
• DL in biomedical engineering
• DL for health informatics
• DL for brain-computer interfaces
• DL for neural rehabilitation engineering
• Related applications


Important Dates:
Submission deadline: August 31, 2023
Reviewing deadline: October 15, 2023
Author revision deadline: November 15, 2023
Final notification date: December 15, 2023


Guest editors
Prof. Larbi Boubchir (Lead GE) – University of Paris 8, France
Email: Larbi.boubchir@univ-paris8.fr

Prof. Elhadj Benkhelifa – Staffordshire University, UK
Email: Benkhelifa@staffs.ac.uk

Prof. Jaime Lloret – Universitat Politecnica de Valencia, Spain
Email: jlloret@dcom.upv.es

Prof. Boubaker Daachi – University of Paris 8, France
Email: boubaker.daachi@univ-paris8.fr

Submission Guidelines:
Authors should prepare their manuscript according to the Instructions for Authors available from the Multimedia Tools and Applications website. Authors should submit through the online submission site at https://www.editorialmanager.com/mtap/default.aspx and select “SI 1239 – Emerging Trends and Applications of Deep Learning for Biomedical Data” when they reach the “Article Type” step in the submission process. Submitted papers should present original, unpublished work, relevant to one of the topics of the special issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least three independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process.

Early registration: Invitation to join 2023 Summer ‘Programming short course and workshop on Deep Learning and Computer Vision’, 30 August – 1 September, 2023

Dear Deep Learning, Computer Vision, Digital Media engineers, scientists and enthusiasts,

  

you are welcomed to register to the  CVML course on ‘Programming short course and workshop on Deep Learning and Computer Vision’,  30th August – 1st September 2023:

https://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-deep-learning-and-computer-vision-2023/

 

It will take place at KEDEA Building, hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece. The course  provides an in-depth presentation of programming tools and techniques for various computer vision and deep learning problems. The target application domains are autonomous systems (e.g., real time object detection) and digital/social media analysis for Natural Disaster Management. The short course consists of three parts (A, B, C), each having lectures and programming workshops with hands-on lab exercises. There will be complemented lecture pdfs, to enable you to study at your own pace. You can also self-assess your knowledge, by filling appropriate questionnaires (one per lecture).

 

This course is part of the very successful CVML programming short course and workshop series that has been taking place in the last four years.

 

Course description ‘Programming short course and workshop on Deep Learning and Computer Vision’

 

The short course consists of three parts (A, B, C), each having lectures and programming workshops with hands-on lab exercises.

 

Part A will focus on Deep Learning and GPU programming. The lectures of this part provide a solid background on Deep Neural Networks (DNN) topics, notably convolutional NNs (CNNs) and deep learning for image classification.

 

Part B lectures will focus on deep learning algorithms for Perception on Autonomous Systems, namely on 2D object/face detection and 2D object tracking.

Part C lectures will focus on Autonomous Systems in Natural Disaster Management (NDM). The lectures will provide a basic understanding of Real-Time Image Segmentation algorithms.

 

 

Course lectures and programming workshops

 

Part A (8 hours) Deep Learning for Autonomous Systems

 

  1. Deep neural networks – Convolutional NNs.
  2. Knowledge Distillation in Deep Neural Networks.
  3. Programming workshop on Deep neural networks – Convolutional NNs.
  4. Programming workshop on Knowledge Distillation in Deep Neural Networks.

 

Part B (8 hours) Autonomous Systems Perception

 

  1. Real Time Object Detection.
  2. 2D Object Tracking in Embedded Systems.
  3. Programming workshop on Real Time Object Detection.
  4. Programming workshop on 2D Object Tracking in Embedded Systems.

 

Part C (8 hours) Autnomous Systems in Natural Disaster Management

 

  1. Real-Time Image Segmentation.
  2. Natural Language Processing for Natural Disaster Management.
  3. Programming workshop on Real-Time Image Segmentation.
  4. Programming workshop on Natural Language Processing for Natural Disaster Management.

 

 

You can use the following link for course registration:

https://rc.auth.gr/product-list/single-product/127

 

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

 

This programming 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+.

  

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)

Aristotle University of Thessaloniki, Greece

 

IEEE NorCAS 2023 Call for Special Sessions and Tutorials

 

The 2023 IEEE Nordic Circuits and Systems Conference (NorCAS) will take place in

Aalborg, Denmark on October 31-November1, 2023. The conference is co-sponsored

by the IEEE Circuits and Systems Society and Tampere University.

 

Special Sessions for NorCAS 2023 can be proposed by June 15, 2023 by email to

norcas@tuni.fi. They will be added to the paper submission system once approved

by the conference management. It is then the responsibility of the session organizers to

promote their session.

 

To propose a Special Session, send the proposed session title/topic, organizer(s) name,

affiliation and email, a short paragraph on the rationale of the session, and the names

and email addresses of five proposed (PhD level) reviewers for the papers submitted to

the session. We expect at least one of the organizers to participate in the conference to

chair the session if accepted.

 

Special Session papers will undergo similar reviews as any other papers submitted to the

conference, and presented papers will be submitted for inclusion in the IEEE Xplore database.

 

We also take proposals for half-day tutorials (at 13-17 on Monday October 30, net time about 3h),

especially on timely digital/System-on-Chip topics. The deadline is the same as for special sessions.

Please describe the title, rationale and content briefly, and provide a short biography of

the tutorial instructor(s). By default one such tutorial will be selected.

 

For more details on IEEE NorCAS 2023, see https://events.tuni.fi/norcas2023

 

Regards,

 

Jari Nurmi (TAU)

IEEE NorCAS General Chair

 

Real-Time Intelligent Systems 2023

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