[visionlist] [CfP] International Workshop on Industrial Machine Learning (in conj. with ICPR)

Francesco Setti francesco.setti at univr.it
Tue May 24 02:55:24 -04 2022

Call for Papers
2nd International Workshop on Industrial Machine Learning
In conjunction with ICPR 2022

Apologies for multiple posting
Please distribute this call to interested parties


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.
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.
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:

  *   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.

Full Paper Submission: June 6, 2022
Notification of Acceptance: June 20, 2022
Camera-Ready Paper Due: August 21, 2022
Workshop date: August 21, 2022

In case of rejection from ICPR main conference, authors can submit their work to the IML workshop including a response to reviewers' comments.

Papers must be prepared according to the ICPR guidelines<https://www.icpr2022.com/submission-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.

All the papers must be submitted using CMT submission server: https://cmt3.research.microsoft.com/IML2022

Luigi Di Stefano, University of Bologna, Italy
Massimiliano Mancini, Univeristy of Tubingen, Germany
Vittorio Murino, University of Verona, Italy
Paolo Rota, University of Trento, Italy
Francesco Setti, University of Verona, Italy

Francesco Setti, Ph.D.
Assistant Professor (RTD-b)
Department of Computer Science
University of Verona
Room 1.64 - Ca' Vignal 2
Strada le Grazie 15 - 37134 Verona (Italy)
Email: francesco.setti at univr.it<mailto:francesco.setti at univr.it>
Homepage: www.franzsetti.info<http://www.franzsetti.info/>

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