Connectionists: CFP (Deadline Extension)- Big Visual Data Analytics (BVDA) Workshop at ICIP, 27-30 October 2024, Abu Dhabi, UAE

[Efi]

*CALL FOR PAPERS*

*Big Visual Data Analytics (BVDA) Workshop** at ICIP 2024*

*IEEE International Conference on Image Processing, 27-30 October 2024, Abu
Dhabi, UAE*


We invite researchers and practitioners working on various aspects of *big
visual data analytics* to submit their work to the *Big Visual Data
Analytics (BVDA) Workshop*, organized in conjunction with the* IEEE
International Conference on Image Processing (ICIP) 2024. *The
ever-increasing visual data availability leads to repositories or streams
characterized by big data volumes, velocity (acquisition and processing
speed), variety (e.g., RGB or RGB-D or hyperspectral images) and complexity
(e.g., video data and point clouds). Their processing necessitates novel
and advanced visual analysis methods, in order to unlock their potential
across diverse domains.

The *BVDA Workshop* aims to explore this rapidly evolving field
encompassing cutting-edge methods, emerging applications, and significant
challenges in extracting meaning and value from large-scale visual
datasets. From high-throughput biomedical imaging and autonomous driving
sensors to satellite imagery and social media platforms, visual data has
permeated nearly every aspect of our lives. Analyzing this data effectively
requires efficient tools that go beyond traditional methods, leveraging
advancements in machine learning, computer vision and data science.
Exciting new developments in these fields are already paving the way for *fully
and semi-automated visual data analysis workflows at an unprecedented
scale.* This workshop will provide a platform for researchers and
practitioners to discuss recent breakthroughs and challenges in big visual
data analytics, explore novel applications across diverse domains (e.g.,
environment monitoring, natural disaster management,  robotics, urban
planning, healthcare, etc.), as well as for fostering interdisciplinary
collaborations between computer vision, data science, machine learning, and
domain experts. Its ultimate goal is to help identify promising research
directions and pave the way for future innovations.

The BVDA Workshop delves deeper into specific aspects of big visual data,
complementing the broader ICIP themes. Thus it can generate new research
interest and collaborations within the main conference community, while
attracting researchers and practitioners specifically interested in big
visual data analytics. Its interdisciplinary nature, its focus on
cutting-edge areas (e.g., large Vision-Language Models, distributed deep
neural architectures, fast generative models, etc.) and its synergies with
neighboring fields (e.g., privacy-preserving analytics, real-time visual
analytics, ethical considerations, etc.) broaden the discussion.

*Topics of interest* include (non-exhaustively) the following ones:

   - Scalable algorithms and architectures for big visual data processing
   and analysis.
   - High-performance computing, distributed and parallel processing,
   efficient data storage and retrieval for big visual data analysis.
   - Deep learning architectures for large-scale visual content
   understanding, search & retrieval: Convolutional Neural Networks (CNNs),
   Transformers, Self-Supervised Learning, etc.
   - Big visual data summarization.
   - Decentralized/distributed DNN architectures for big visual data
   analysis.
   - Cloud/edge computing architectures for big visual data analysis.
   - Multimodal big visual data analysis.
   - Large Vision-Language Models/Foundation Models.
   - Fast generative models for visual data: Synthesizing realistic
   images/videos, data augmentation, in-painting and manipulation.
   - Fast Interpretability and eXplainability (XAI) of visual analytics
   models: Understanding and communicating model decisions, trust and bias in
   AI systems.
   - Privacy-preserving analytics in the context of big visual data: Secure
   data processing, differential privacy, federated learning.
   - Visual analytics for real-time applications: Efficient analysis of
   visual streaming data, edge/fog computing.
   - Visual analytics for specialized domains: Remote sensing, natural
   disaster management, medical imaging, social media analysis, etc.
   - Ethical considerations in big visual data analytics: Data ownership,
   fairness, accountability, societal impact.


The regular ICIP paper template/style must be used for submission. All
accepted contributions will be *published in IEEE Xplore*. The paper
submission deadline is *May* *13, 2024*.

*For further details and submission instructions visit: *
https://icarus.csd.auth.gr/cfp-bvda-icip24-workshop/


Organizers

Prof. Ioannis Pitas: Chair of the International AI Doctoral Academy (AIDA
<https://www.i-aida.org/>), Director of the Artificial Intelligence and
Information analysis (AIIA <https://aiia.csd.auth.gr/>) Lab,
Aristotle University of Thessaloniki, Greece.

Prof. Massimo Villari: University of Messina, Italy.

Dr. Ioannis Mademlis: Postdoctoral researcher at the Harokopio University
of Athens.
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