A method for pre-sorting mixed mail using convolutional neural networks and transfer learning

Michael Schadler; Dominik Stadlthanner; Bastian Mayer; Michael Schedler; Christian Landschützer

A method for pre-sorting mixed mail using convolutional neural networks and transfer learning

Titel in Übersetzung: Ein Verfahren zur Vorsortierung von Postsendungen mittels faltenden neuronalen Netzen und Transferlernen

Michael Schadler, Dominik Stadlthanner, Bastian Mayer, Michael Schedler, Christian Landschützer

Institut für Technische Logistik (3090)

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Abstract

Sorting mixed mail has become increasingly important for postal service
providers. Low-value consignments, that have unfavorable material
properties, such as odd shape or flexibility, have increased in terms of
volume in recent years and cause substantial problems in sorting
processes. In order to automate the sorting of mixed-mail items the so-
called ‘Free-Fall-Sorter’ was developed at the Institute of Logistics
Engineering at Graz University of Technology. In this paper, an image
classification system is proposed to pre-sort mixed mail for this new
machine. The computer vision system used for the experiments applies
transfer learning to a publicly available convolutional neural network
called ‘MobileNet V2’. The classification system is designed to be
composed of low-cost hardware components, yet capable of providing
real-time inference. The results show a high accuracy of the re-trained
model.

Titel in Übersetzung	Ein Verfahren zur Vorsortierung von Postsendungen mittels faltenden neuronalen Netzen und Transferlernen
Originalsprache	englisch
Titel	MHCL 2022
Untertitel	XXIV International Conference on "Material Handling, Constructions and Logistics" September 21st - 23rd, 2022, Belgrade
Erscheinungsort	Belgrade
Herausgeber (Verlag)	Faculty of Mechanical Engineering, Belgrade University
Seiten	71-80
Seitenumfang	10
ISBN (Print)	978-86-6060-134-8
Publikationsstatus	Veröffentlicht - Sept. 2022
Veranstaltung	24th International Conference on Material Handling, Contructions and Logistics: MHCL 2022 - Faculty of mechanical Engineering - University Belgrade, Belgrad, Serbien Dauer: 21 Sept. 2022 → 23 Sept. 2022 https://www.mhcl.info

Konferenz

Konferenz	24th International Conference on Material Handling, Contructions and Logistics
Land/Gebiet	Serbien
Ort	Belgrad
Zeitraum	21/09/22 → 23/09/22
Anderes	XXIV International Conference on Material Handling, Contructions and Logistics
Internetadresse	https://www.mhcl.info

Schlagwörter

polybag
Convolutional neural networks (CNNs)
image classification
deep learning
low-value consignment

Fields of Expertise

Mobility & Production

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

A method for pre-sorting mixed mail using convolutional neural networks and transfer learning
Michael Schadler (Redner/in)
21 Sept. 2022 → 23 Sept. 2022
Aktivität: Vortrag oder Präsentation › Vortrag bei Konferenz oder Fachtagung › Science to science

Dieses zitieren

Schadler, M., Stadlthanner, D., Mayer, B., Schedler, M., & Landschützer, C. (2022). A method for pre-sorting mixed mail using convolutional neural networks and transfer learning. in MHCL 2022: XXIV International Conference on "Material Handling, Constructions and Logistics" September 21st - 23rd, 2022, Belgrade (S. 71-80). Faculty of Mechanical Engineering, Belgrade University.

A method for pre-sorting mixed mail using convolutional neural networks and transfer learning. / Schadler, Michael ; Stadlthanner, Dominik; Mayer, Bastian et al.
MHCL 2022: XXIV International Conference on "Material Handling, Constructions and Logistics" September 21st - 23rd, 2022, Belgrade. Belgrade: Faculty of Mechanical Engineering, Belgrade University, 2022. S. 71-80.

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Schadler, M , Stadlthanner, D, Mayer, B, Schedler, M & Landschützer, C 2022, A method for pre-sorting mixed mail using convolutional neural networks and transfer learning. in MHCL 2022: XXIV International Conference on "Material Handling, Constructions and Logistics" September 21st - 23rd, 2022, Belgrade. Faculty of Mechanical Engineering, Belgrade University, Belgrade, S. 71-80, 24th International Conference on Material Handling, Contructions and Logistics, Belgrad, Serbien, 21/09/22.

Schadler M , Stadlthanner D, Mayer B, Schedler M, Landschützer C. A method for pre-sorting mixed mail using convolutional neural networks and transfer learning. in MHCL 2022: XXIV International Conference on "Material Handling, Constructions and Logistics" September 21st - 23rd, 2022, Belgrade. Belgrade: Faculty of Mechanical Engineering, Belgrade University. 2022. S. 71-80

Schadler, Michael ; Stadlthanner, Dominik ; Mayer, Bastian et al. / A method for pre-sorting mixed mail using convolutional neural networks and transfer learning. MHCL 2022: XXIV International Conference on "Material Handling, Constructions and Logistics" September 21st - 23rd, 2022, Belgrade. Belgrade : Faculty of Mechanical Engineering, Belgrade University, 2022. S. 71-80

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title = "A method for pre-sorting mixed mail using convolutional neural networks and transfer learning",

abstract = "Sorting mixed mail has become increasingly important for postal serviceproviders. Low-value consignments, that have unfavorable materialproperties, such as odd shape or flexibility, have increased in terms ofvolume in recent years and cause substantial problems in sortingprocesses. In order to automate the sorting of mixed-mail items the so-called {\textquoteleft}Free-Fall-Sorter{\textquoteright} was developed at the Institute of LogisticsEngineering at Graz University of Technology. In this paper, an imageclassification system is proposed to pre-sort mixed mail for this newmachine. The computer vision system used for the experiments appliestransfer learning to a publicly available convolutional neural networkcalled {\textquoteleft}MobileNet V2{\textquoteright}. The classification system is designed to becomposed of low-cost hardware components, yet capable of providingreal-time inference. The results show a high accuracy of the re-trainedmodel.",

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PY - 2022/9

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N2 - Sorting mixed mail has become increasingly important for postal serviceproviders. Low-value consignments, that have unfavorable materialproperties, such as odd shape or flexibility, have increased in terms ofvolume in recent years and cause substantial problems in sortingprocesses. In order to automate the sorting of mixed-mail items the so-called ‘Free-Fall-Sorter’ was developed at the Institute of LogisticsEngineering at Graz University of Technology. In this paper, an imageclassification system is proposed to pre-sort mixed mail for this newmachine. The computer vision system used for the experiments appliestransfer learning to a publicly available convolutional neural networkcalled ‘MobileNet V2’. The classification system is designed to becomposed of low-cost hardware components, yet capable of providingreal-time inference. The results show a high accuracy of the re-trainedmodel.

AB - Sorting mixed mail has become increasingly important for postal serviceproviders. Low-value consignments, that have unfavorable materialproperties, such as odd shape or flexibility, have increased in terms ofvolume in recent years and cause substantial problems in sortingprocesses. In order to automate the sorting of mixed-mail items the so-called ‘Free-Fall-Sorter’ was developed at the Institute of LogisticsEngineering at Graz University of Technology. In this paper, an imageclassification system is proposed to pre-sort mixed mail for this newmachine. The computer vision system used for the experiments appliestransfer learning to a publicly available convolutional neural networkcalled ‘MobileNet V2’. The classification system is designed to becomposed of low-cost hardware components, yet capable of providingreal-time inference. The results show a high accuracy of the re-trainedmodel.

KW - polybag

KW - Convolutional neural networks (CNNs)

KW - image classification

KW - deep learning

KW - low-value consignment

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EP - 80

BT - MHCL 2022

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ER -

A method for pre-sorting mixed mail using convolutional neural networks and transfer learning

Abstract

Konferenz

Schlagwörter

Fields of Expertise

UN SDGs

Aktivitäten

A method for pre-sorting mixed mail using convolutional neural networks and transfer learning

Dieses zitieren