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<font face="Candara">Apologize for multiple postings<br>
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Call for Papers<br>
<br>
2nd International Workshop on Industrial Machine Learning<br>
<br>
In conjunction with ICPR 2022<br>
<a class="moz-txt-link-freetext" href="https://sites.google.com/view/iml2022">https://sites.google.com/view/iml2022</a><br>
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AIMS AND SCOPE<br>
==============<br>
With the advent of Industry 4.0 and Smart Manufacturing paradigms,
data has become a valuable resource, and very often an asset, for
every manufacturing company. Data from the market, from machines,
from warehouses and many other sources are now cheaper than ever
to be collected and stored. A study from Juniper Research has
identified industrial internet of things (IIoT) as a key growth
market over the next five years, accounting for an increase in the
global number of IIoT connections from 17.7 billion in 2020 to
36.8 billion in 2025, representing an overall growth rate of 107%.
With such an amount of data produced every second, classical data
analysis approaches are not useful and only automated learning
methods can be applied to produce value, a market estimated in
more than 200B$ worldwide. Using machine learning techniques
manufacturers can exploit data to significantly impact their
bottom line by greatly improving production efficiency, product
quality, and employee safety.<br>
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The introduction of ML to industry has many benefits that can
result in advantages well beyond efficiency improvements, opening
doors to new opportunities for both practitioners and researchers.
Some direct applications of ML in manufacturing include predictive
maintenance, supply chain management, logistics, quality control,
human-robot interaction, process monitoring, anomaly detection and
root cause analysis to name a few.<br>
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This workshop will ground on the successful story of the first
edition, with 19 oral presentations and 3 invited talks, to draw
attention to the importance of integrating ML technologies and
ML-based solutions into the manufacturing domain, while addressing
the challenges and barriers to meet the specific needs of this
sector. Workshop participants will have the chance to discuss:<br>
- needs and barriers for ML in manufacturing<br>
- state-of-the-art in ML applications to manufacturing<br>
- future research opportunities in this domain<br>
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TOPICS OF INTEREST<br>
=================<br>
This is an open call for papers, soliciting original contributions
considering recent findings in theory, methodologies, and
applications in the field of industrial machine learning. Position
papers presenting industrial use cases and discussing potential
solutions are welcome. Potential topics include, but are not
limited to:<br>
<br>
- Robustness-oriented learning algorithms<br>
- Machine learning for robotics (e.g. learning from
demonstration)<br>
- Continuous and life-long learning for industrial
applications<br>
- Transfer learning and domain adaptation<br>
- Anomaly detection and process monitoring<br>
- ML applications to Predictive Maintenance<br>
- ML applications to Supply Chain and Logistics<br>
- ML applications to Quality Control<br>
- ML for flexible manufacturing<br>
- Deep Learning for industrial applications<br>
- Learning from Big-Data<br>
- Inference in real-time applications<br>
- Machine Learning on Embedded and Edge computing hardware<br>
<br>
All the contributions are expected to expose applications to the
industrial sector, possibly with real world case studies. Position
papers presenting new industrial systems and case studies,
possibly reporting preliminary validation studies, are also
encouraged.<br>
<br>
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IMPORTANT DATES<br>
================<br>
Full Paper Submission: June 6, 2022<br>
Notification of Acceptance: June 20, 2022<br>
Camera-Ready Paper Due: June 30, 2022<br>
Workshop date: August 21, 2022<br>
</font><br>
<font face="Candara"><span style="font-family: 'Open Sans';
font-size: 12pt; font-style: normal; font-variant: normal;
font-weight: normal; text-decoration: normal; vertical-align:
baseline;">In case of rejection from ICPR main conference,
authors can submit their work to the IML workshop. Authors
should address all ICPR reviewers' comments in the submitted
paper and submit the ICPR reviews as supplementary material.</span><br>
<br>
<br>
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SUBMISSION GUIDELINES<br>
=====================<br>
Papers must be prepared according to the ICPR guidelines. All
papers will be reviewed by at least two reviewers with
single-blind peer review policy. Papers will be selected based on
relevance, significance and novelty of results, technical merit,
and clarity of presentation. Papers will be published in ICPR
proceedings.<br>
All the papers must be submitted using CMT submission server:
<a class="moz-txt-link-freetext" href="https://cmt3.research.microsoft.com/IML2022">https://cmt3.research.microsoft.com/IML2022</a><br>
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ORGANIZING COMMITTEE<br>
=====================<br>
Luigi Di Stefano, University of Bologna, Italy<br>
Massimiliano Mancini, Univeristy of Tubingen, Germany<br>
Vittorio Murino, University of Verona, Italy<br>
Paolo Rota, University of Trento, Italy<br>
Francesco Setti, University of Verona, Italy<br>
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<pre class="moz-signature" cols="72">--
Vittorio Murino
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Prof. Vittorio Murino, Ph.D.
PAVIS - Pattern Analysis & Computer Vision
Istituto Italiano di Tecnologia
via Enrico Melen 83, Building B, Floor 8
16152 Genova, Italy
Mobile: +39 329 6508554
E-mail: <a class="moz-txt-link-abbreviated" href="mailto:vittorio.murino@iit.it">vittorio.murino@iit.it</a>
Secretary: Sara Curreli
email: <a class="moz-txt-link-abbreviated" href="mailto:sara.curreli@iit.it">sara.curreli@iit.it</a>
Phone: +39 010 2897420
<a class="moz-txt-link-freetext" href="http://pavis.iit.it">http://pavis.iit.it</a>
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