[visionlist] CFP: International workshop on Industrial Machine Learning (IML), co-located with ICPR2020

Francesco Setti francesco.setti at univr.it
Fri Jul 3 05:00:40 -04 2020

(apologise for multiple copies)
1st International Workshop on Industrial Machine Learning**
*in conjunction with ICPR 2020
January 11, 2020 - Milan, Italy

Website: _https://sites.google.com/view/iml2020_

Submission deadline: September 25th, 2020
Submission server: _https://cmt3.research.microsoft.com/IWIML2020_

With the advent of Industry 4.0 paradigm, data has become a valuable 
resource, and very often an asset, for every manufacturer. Data from the 
market, from machines, from warehouses and many other sources are now 
cheaper than ever to be collected and stored. It has been estimated that 
in 2020 we will have more than 50B devices connected to the Industrial 
Internet of Things, generating more than 500ZB of data. With such an 
amount of data, 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. Through the use of 
machine learning techniques manufacturers can use data to significantly 
impact their bottom line by greatly improving production efficiency, 
product quality, and employee safety.
The introduction of ML in 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.

This workshop will 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:
- needs and barriers for ML in manufacturing
- state-of-the-art in ML applications to manufacturing
- future research opportunities in this domain

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:

  * Robustness-oriented learning algorithms
  * Machine learning for robotics (e.g. learning from demonstration)
  * Continuous and life-long learning for industrial applications
  * Transfer learning and domain adaptation
  * Anomaly detection and process monitoring
  * ML applications to Predictive Maintenance
  * ML applications to Supply Chain and Logistics
  * ML applications to Quality Control
  * ML for flexible manufacturing
  * Deep Learning for industrial applications
  * Learning from Big-Data
  * Inference in real-time applications
  * Machine Learning on Embedded and Edge computing hardware

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.

Papers will be limited to 6 pages according to ICPR format (c.f. Main 
conference authors guidelines). All papers will be reviewed by at least 
two reviewers with double blind 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.
All the papers must be submitted using CMT server: 


  * Full Paper Submission: September 25, 2020
  * Notification of Acceptance: November 10, 2020
  * Camera-Ready Paper Due : November 15, 2020

In case of rejection from ICPR main conference, authors can submit their 
work to the IML workshop by October 10, 2020. Authors should address all 
ICPR reviewers' comments in the submitted paper and submit the ICPR 
reviews as supplementary material.

Luigi Di Stefano (University of Bologna, Italy)
Massimiliano Mancini (la Sapienza University, Italy)
Vittorio Murino (University of Verona, Italy)
Paolo Rota (University of Trento, Italy)
Francesco Setti (University of Verona, Italy)

For any inquiry regarding the workshop please contact Francesco Setti at 
_francesco.setti at univr.it

Please distribute this call to interested parties

Francesco Setti, Ph.D.
Assistant Professor (RTD-a)
Department of Computer Science
University of Verona
Room 1.64 - Ca' Vignal 2
Strada le Grazie 15 - 37134 Verona (Italy)
Phone: +39 045 802 7804
Email: francesco.setti at univr.it
Homepage: www.franzsetti.info

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