[hpc-announce] ANNEI 2024 (Co-Sponsored by IEEE): The International workshop on Artificial Neural Networks for Edge Intelligence, Malmö, Sweden. September 2-5, 2024

[Stanley Ewenike]

[Apologies if you got multiple copies of this invitation]

*The International workshop on Artificial Neural Networks for Edge
Intelligence (ANNEI 2024)*

Co-located with

The 9th International Conference on Fog and Mobile Edge Computing (FMEC
2024)

https://urldefense.us/v3/__https://emergingtechnet.org/FMEC2024/Workshops/ANNEI2024/index.html__;!!G_uCfscf7eWS!dyf0Q3763DNo8kMhJ6aoQmObegI6W9x2ac4tFqwk44rvnVmP4kgpdUVHEjR510_rAtS0q2x4HNH8M1izsjg0t1pHZj1hqEzUhQ$ 

Malmö, Sweden. September 2-5, 2024

Technically Co-Sponsored by IEEE Sweden Section

*ANNEI 2024 CFP:*

Welcome to the International workshop on Artificial Neural Networks for
Edge Intelligence (ANNEI 2024). The workshop will discuss artificial
intelligence (AI) optimization and its implementation in edge computing and
Internet of Things (IoT) environments, with a focus on federated learning,
artificial neural networks, and sparse neural networks. Federated Learning
investigates a cooperative method that protects data privacy while allowing
AI models to be trained over dispersed edge devices. Sparse ANNs are a
viable option that can be deployed in edge computing/IoT scenarios since
they address scalability issues and reduce energy usage. Sparsity
approaches also allow the topology of ANNs to be smaller and more scalable,
which makes them appropriate for deployment in resource-constrained
situations like edge computing and IoT devices. Multidisciplinary research
that combines edge computing with other emerging technologies, such as
blockchain, artificial intelligence, cybersecurity technologies, etc., is
highly welcomed. The potential topics include, but are not limited to:

   - Federated Learning: Privacy-Preserving Collaborative AI Training on
   Edge Devices.
   - Sparse Neural Networks: Principles, Advantages, and Applications in
   Edge Computing and IoT.
   - Optimization Techniques for AI Models in Resource-Constrained
   Environments.
   - Scalability Challenges and Solutions in Edge Computing and IoT
   Deployments.
   - Energy-Efficient Computing Strategies for Edge Devices and IoT Systems.
   - Exploring the Interplay between Federated Learning and Edge Computing
   Technologies.
   - Security and Privacy Considerations in Federated Learning and Edge AI
   Systems.
   - Real-world Case Studies of Federated Learning and Sparse Neural
   Networks in Edge Computing.
   - Integration of Edge Computing with Blockchain Technology for Secure
   and De-centralized AI Applications.
   - Advances in Cyber-security Technologies for Securing Edge
   Computing/IoT Environments.
   - Hardware Acceleration and Edge Computing Architectures for Efficient
   AI Inference.
   - Federated Learning for Healthcare Applications: Challenges and
   Opportunities.
   - Exploring Edge Computing and AI Integration in Smart Cities and Urban
   Infrastructure.
   - Future Directions and Emerging Trends in Edge Computing and IoT
   Integration with AI Technologies.

*Submissions Guidelines and Proceedings*

Manuscripts should be prepared in 10-point font using the IEEE 8.5" x 11"
two-column format. All papers should be in PDF format, and submitted
electronically at Paper Submission Link. A full paper can be up to 8 pages
(including all figures, tables and references). Submitted papers must
present original unpublished research that is not currently under review
for any other conference or journal. Papers not following these guidelines
may be rejected without review. Also submissions received after the due
date, exceeding length limit, or not appropriately structured may also not
be considered. Authors may contact the Program Chair for further
information or clarification. All submissions are peer-reviewed by at least
three reviewers. Accepted papers will appear in the FMEC Proceeding, and be
published by the IEEE Computer Society Conference Publishing Services and
be submitted to IEEE Xplore for inclusion.

Submitted papers must include original work, and must not be under
consideration for another conference or journal. Submission of regular
papers up to 8 pages and must follow the IEEE paper format. Please include
up to 7 keywords, complete postal and email address, and fax and phone
numbers of the corresponding author. Authors of accepted papers are
expected to present their work at the conference. Submitted papers that are
deemed of good quality but that could not be accepted as regular papers
will be accepted as short papers. Length of short papers can be between 4
to 6 pages.

*Important Dates:*

Submission Due: June 30th, 2024

Notification: July 30th, 2024

Camera-ready submission: August 10th, 2024



*Organization Committee*

   - Dr. Lucia Cavallaro, Radboud University, The Netherlands
   - Dr. Muhammad Azfar Yaqub, Free University of Bozen-Bolzano, Italy
   - Dr. Antonio Liotta, Free University of Bozen-Bolzano, Italy



*Contact:*

Please send any inquiry to :

Lucia Cavallaro <lucia.cavallaro at ru.nl>

Liotta Antonio <Antonio.Liotta at unibz.it>

Yaqub Muhammad Azfar <MuhammadAzfar.Yaqub at unibz.it>