<div dir="ltr"><div style="border:0px;font-variant-numeric:inherit;font-variant-east-asian:inherit;font-variant-alternates:inherit;font-stretch:inherit;font-size:14px;line-height:inherit;font-family:Arial;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(36,36,36);text-align:center"><b style="font-family:"Times New Roman",serif;font-size:12pt;font-style:inherit;font-variant-ligatures:inherit;font-variant-caps:inherit">CALL FOR PAPERS</b></div><p align="center" style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b><i> </i></b></span></p><p align="center" style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:14pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b><i>Big Visual Data Analytics (BVDA) Workshop</i></b></span><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b> at </b></span><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:14pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b>ICIP 2024</b></span></p><p align="center" style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b> </b></span></p><p align="center" style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b>IEEE International Conference on Image Processing, 27-30 October 2024, Abu Dhabi, UAE</b></span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b> </b></span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:6pt 0px 0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black">We invite researchers and practitioners working on various aspects of <b>big visual data analytics</b> to submit their work to the <b>Big Visual Data Analytics (BVDA) Workshop</b>, organized in conjunction with the<b> IEEE International Conference on Image Processing (ICIP) 2024. </b>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.</span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:6pt 0px 0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black">The <b>BVDA Workshop</b> 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 <b>fully and semi-automated visual data analysis workflows at an unprecedented scale.</b> 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.</span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:6pt 0px 0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black">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.</span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b> </b></span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b>Topics of interest</b> include (non-exhaustively) the following ones:</span></p><ul style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin-top:0px;margin-right:0px;padding-left:0px"><li style="color:black;font-size:12pt;font-family:Aptos,Aptos_EmbeddedFont,Aptos_MSFontService,Calibri,Helvetica,sans-serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Scalable algorithms and architectures for big visual data processing and analysis.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">High-performance computing, distributed and parallel processing, efficient data storage and retrieval for big visual data analysis.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Deep learning architectures for large-scale visual content understanding, search & retrieval: Convolutional Neural Networks (CNNs), Transformers, Self-Supervised Learning, etc.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Big visual data summarization.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Decentralized/distributed DNN architectures for big visual data analysis.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Cloud/edge computing architectures for big visual data analysis.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Multimodal big visual data analysis.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Large Vision-Language Models/Foundation Models.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Fast generative models for visual data: Synthesizing realistic images/videos, data augmentation, in-painting and manipulation.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Fast Interpretability and eXplainability (XAI) of visual analytics models: Understanding and communicating model decisions, trust and bias in AI systems.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Privacy-preserving analytics in the context of big visual data: Secure data processing, differential privacy, federated learning.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Visual analytics for real-time applications: Efficient analysis of visual streaming data, edge/fog computing.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Visual analytics for specialized domains: Remote sensing, natural disaster management, medical imaging, social media analysis, etc.</span></li><li style="color:black;font-size:12pt;font-family:"Times New Roman",serif;margin:0px 0px 0px 36pt"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:inherit">Ethical considerations in big visual data analytics: Data ownership, fairness, accountability, societal impact.</span></li></ul><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b> </b></span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black">The regular ICIP paper template/style must be used for submission. All accepted contributions will be <b>published in IEEE Xplore</b>. The paper submission deadline is <b>April 25, 2024</b>.</span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b> </b></span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><b>For further details and submission instructions visit: </b></span><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:11pt;line-height:inherit;font-family:Calibri,sans-serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black"><a href="https://icarus.csd.auth.gr/cfp-bvda-icip24-workshop/" target="_blank" rel="noopener noreferrer" id="gmail-OWA6705e245-1e22-4bd0-0bd7-56170ab122a8" name="x_OWA6705e245-1e22-4bd0-0bd7-56170ab122a8" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline">https://icarus.csd.auth.gr/cfp-bvda-icip24-workshop/</a></span></p><p aria-hidden="true" style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"> </p><p aria-hidden="true" style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"> </p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black">Organizers</span></p><p aria-hidden="true" style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px"> </p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;text-align:justify;margin:0px;line-height:1.2"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black">Prof. Ioannis Pitas: Chair of the International AI Doctoral Academy (<a href="https://www.i-aida.org/" target="_blank" rel="noopener noreferrer" id="gmail-LPlnk555989" title="https://www.i-aida.org/" name="x_LPlnk555989" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline">AIDA</a>), Director of the Artificial Intelligence and Information analysis (<a href="https://aiia.csd.auth.gr/" target="_blank" rel="noopener noreferrer" id="gmail-LPlnk201418" title="https://aiia.csd.auth.gr/" name="x_LPlnk201418" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline">AIIA</a>) Lab,</span></p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px;line-height:1.2"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black">Aristotle University of Thessaloniki, Greece.</span></p><p aria-hidden="true" style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px;line-height:1.2"> </p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px;line-height:1.2"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black">Prof. Massimo Villari: University of Messina, Italy.</span></p><p aria-hidden="true" style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px;line-height:1.2"> </p><p style="color:rgb(36,36,36);font-family:Arial;font-size:15px;margin:0px;line-height:1.2"><span style="border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:"Times New Roman",serif;font-kerning:inherit;font-feature-settings:inherit;margin:0px;padding:0px;vertical-align:baseline;color:black">Dr. Ioannis Mademlis: Postdoctoral researcher at the Harokopio University of Athens.</span></p></div>