[visionlist] CFP - Big Visual Data Analytics (BVDA) Workshop at ICIP, 27-30 October 2024, Abu Dhabi, UAE

[Ioanna Koroni]

*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 9, 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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