<div dir="ltr"><p class="MsoNormal" align="center" style="text-align:center;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">CALL FOR PAPERS</span></b></p>
<p class="MsoNormal" align="center" style="text-align:center;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Special Issue on “Advancing Visual
Data Analytics for Disaster Management”<br>
<i>IMAGE AND VISION COMPUTING</i></span></b></p>
<p class="MsoNormal" align="center" style="text-align:center;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif"> </span></b></p>
<p class="MsoNormal" align="center" style="text-align:center;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><i><span style="font-family:Calibri,sans-serif">Visit the </span></i><span lang="EL" style="font-family:Calibri,sans-serif"><a href="https://www.sciencedirect.com/special-issue/322678/advancing-visual-data-analytics-for-disaster-management" style="color:rgb(70,120,134)"><i><span lang="EN-US">Website</span></i></a></span><span style="font-family:Calibri,sans-serif"></span></p>
<p class="MsoNormal" align="center" style="text-align:center;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><i><span style="font-family:Calibri,sans-serif"> </span></i></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">From
torrents of satellite imagery to drone video streams and citizen-generated
footage, visual data now shapes how we forecast, respond to, and recover from
catastrophes. This Special Issue of <b>Image and Vision Computing</b> journal
seeks state-of-the-art research that converts these heterogeneous visual
streams into trustworthy, real-time intelligence for natural- and human-made
disaster management. We welcome breakthroughs in <b>computer vision</b>, <b>machine
learning</b>, <b>multimodal fusion</b>, <b>privacy-preserving analytics</b>, <b>explainability</b>,
<b>high-performance/edge computing</b>, and <b>generative simulation</b>. Join
us in building a cross-disciplinary forum where novel algorithms meet
operational challenges, advancing resilience and saving lives through <b>smarter
visual data analytics</b>.</span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span lang="EL" style="font-family:Calibri,sans-serif"> </span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">With
the increasing frequency and severity of natural and man-made disasters,
effective disaster management is a global priority. Visual data from any source
play a vital role in disaster preparedness, response, and recovery. Efficient
and accurate analysis of this visual data is crucial for understanding disaster
scale and impact, while having significant implications for broader challenges
in visual data analytics.</span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span lang="EL" style="font-family:Calibri,sans-serif"> </span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">This
<b>Special Issue</b> on “<b>Advancing Visual Data Analytics for Disaster
Management</b>” seeks to present cutting-edge methodologies, emerging
applications, and core challenges in deriving actionable insights from visual
data in disaster contexts. Emphasis is placed on advanced computer vision,
machine learning, and data science methods for processing visual data streams
in real-time or near-real-time, supporting <b>disaster prediction</b>, <b>detection</b>,
<b>monitoring</b>, and <b>assessment</b>.</span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span lang="EL" style="font-family:Calibri,sans-serif"> </span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">The
Special Issue offers a forum for discussing challenges in visual data analytics
with a primary focus on <b>disaster management</b>. Potential applications
include, not exhaustively, flood monitoring, wildfire tracking, earthquake
damage assessment, and urban disaster response. The aim is to foster
collaboration across disciplines – computer vision, machine learning, data
science – and identify future research directions.</span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span lang="EL" style="font-family:Calibri,sans-serif"> </span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">We
welcome submissions on novel <b>algorithms</b>, <b>methods</b>, and <b>systems</b>
for visual data analytics with direct relevance to disaster management or
similarly <b>critical real-world scenarios</b>.</span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span lang="EL" style="font-family:Calibri,sans-serif"> </span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Topics
of interest</span></b><span style="font-family:Calibri,sans-serif"> include,
but are not limited to:</span></p>
<ul style="margin-top:0cm;margin-bottom:0cm" type="disc">
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">Advanced <b>deep learning</b>
models for understanding complex visual data in critical scenarios.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Real-time analytics</span></b><span style="font-family:Calibri,sans-serif">
of visual data from UAVs, satellites, and social media for disaster
response and similar applications.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Visual data summarization</span></b><span style="font-family:Calibri,sans-serif">
and feature extraction for rapid disaster assessment.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Human-centered visual
recognition</span></b><span style="font-family:Calibri,sans-serif"> methods for disaster
scenarios.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Multimodal visual data analysis</span></b><span style="font-family:Calibri,sans-serif">
integrating sources like hyperspectral imaging, LIDAR, and thermal
imaging.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Generative models</span></b><span style="font-family:Calibri,sans-serif">
for visual data: simulation of disaster scenarios, in-painting, and
handling incomplete data.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Explainable and interpretable
models</span></b><span style="font-family:Calibri,sans-serif"> to support decision-making in high-stakes
environments.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Privacy-preserving visual</span></b><span style="font-family:Calibri,sans-serif">
analytics using methods like differential privacy and federated learning.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Scalable algorithms and
architectures</span></b><span style="font-family:Calibri,sans-serif"> for large-scale visual data
processing in disasters.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">High-performance and parallel
computing</span></b><span style="font-family:Calibri,sans-serif"> approaches for visual data
analytics.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Domain-specific analytics</span></b><span style="font-family:Calibri,sans-serif">
for remote sensing, wildfire detection, flood mapping, earthquake damage,
etc.</span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Ethical considerations</span></b><span style="font-family:Calibri,sans-serif">
in visual analytics for disaster management.</span></li>
</ul>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span lang="EL" style="font-family:Calibri,sans-serif"> </span></b></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Submission
Guidelines:</span></b></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">The
Journal's submission system (</span><span lang="EL" style="font-family:Calibri,sans-serif"><a href="https://www.editorialmanager.com/imavis/default.aspx" style="color:rgb(70,120,134)"><span lang="EN-US">Editorial Manager</span></a></span><span style="font-family:Calibri,sans-serif">) will be open for submissions to our
Special Issue from July 1st, 2025. Please refer to the Guide for Authors to
prepare your manuscript and select the article type of “<b>VSI: Visual Data for
DM</b>” when submitting your manuscript online. Both the Guide for Authors and
the submission portal could be found on the Journal Homepage: </span><span lang="EL" style="font-family:Calibri,sans-serif"><a href="https://www.elsevier.com/journals/image-and-vision-computing/0262-8856/guide-for-authors" style="color:rgb(70,120,134)"><span lang="EN-US">Guide for authors - Image and Vision
Computing - ISSN 0262-8856 (elsevier.com)</span></a></span><span style="font-family:Calibri,sans-serif">.</span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">Submissions
must follow the IMAGE AND VISION COMPUTING journal’s formatting and submission
requirements. All manuscripts will undergo rigorous peer review. Contributions
must be original and unpublished, focusing on visual data analytics methods and
their applications in disaster management.</span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span lang="EL" style="font-family:Calibri,sans-serif"> </span></b></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Important
Dates:</span></b><span style="font-family:Calibri,sans-serif"></span></p>
<ul style="margin-top:0cm;margin-bottom:0cm" type="disc">
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">Manuscript Submission Open
Date: <b>July 1st, 2025</b></span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">Manuscript Submission Deadline:
<b>October 31st, 2025</b></span></li>
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">Editorial Acceptance Deadline: <b>February
28th, 2026</b></span></li>
</ul>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span lang="EL" style="font-family:Calibri,sans-serif"> </span></b></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><b><span style="font-family:Calibri,sans-serif">Guest
Editors:</span></b></p>
<ol style="margin-top:0cm;margin-bottom:0cm" start="1" type="1">
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">Prof.
Ioannis Pitas (Department of Informatics, Aristotle University of
Thessaloniki, Greece)</span></li>
</ol>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><i><span style="font-family:Calibri,sans-serif">e-mail
address: </span></i><span lang="EL" style="font-family:Calibri,sans-serif"><a href="mailto:pitas@csd.auth.gr" style="color:rgb(70,120,134)"><i><span lang="EN-US">pitas@csd.auth.gr</span></i></a></span><i><u><span style="font-family:Calibri,sans-serif"></span></u></i></p>
<ol style="margin-top:0cm;margin-bottom:0cm" start="2" type="1">
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">Prof.
Jose Ramiro Martinez de Dios (Robotics, Vision and Control Group,
University of Seville, Spain)</span></li>
</ol>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><i><span style="font-family:Calibri,sans-serif">e-mail
address: </span></i><span lang="EL" style="font-family:Calibri,sans-serif"><a href="mailto:jdedios@us.es" style="color:rgb(70,120,134)"><i><span lang="EN-US">jdedios@us.es</span></i></a></span><i><u><span style="font-family:Calibri,sans-serif"></span></u></i></p>
<ol style="margin-top:0cm;margin-bottom:0cm" start="3" type="1">
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">Prof.
Stefano Berretti (Media Integration and Communication Center, University
of Florence, Italy)</span><span lang="EN-AU" style="font-family:Calibri,sans-serif"></span></li>
</ol>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><i><span style="font-family:Calibri,sans-serif">e-mail
address: </span></i><span lang="EL" style="font-family:Calibri,sans-serif"><a href="mailto:stefano.berretti@unifi.it" style="color:rgb(70,120,134)"><i><span lang="EN-US">stefano.berretti@unifi.it</span></i></a></span><i><u><span style="font-family:Calibri,sans-serif"></span></u></i></p>
<ol style="margin-top:0cm;margin-bottom:0cm" start="4" type="1">
<li class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">Dr.
Ioannis Mademlis (Department of Informatics, Aristotle University of
Thessaloniki, Greece)</span></li>
</ol>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><i><span style="font-family:Calibri,sans-serif">e-mail
address: </span></i><span lang="EL" style="font-family:Calibri,sans-serif"><a href="mailto:imademlis@csd.auth.gr" style="color:rgb(70,120,134)"><i><span lang="EN-US">imademlis@csd.auth.gr</span></i></a></span><i><u><span style="font-family:Calibri,sans-serif"></span></u></i></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span lang="EL" style="font-family:Calibri,sans-serif"> </span></p>
<p class="MsoNormal" style="text-align:justify;margin:0cm;font-size:12pt;font-family:Aptos,sans-serif"><span style="font-family:Calibri,sans-serif">We
look forward to your contributions to this Special Issue on advancing visual
data analytics for more effective disaster management and similar real-world
applications.</span></p></div>