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12/02/2021 - 12/02/2021 | online

Application of deep learning image recognition techniques for characterization of thin coatings

For the last time this year, on December 2nd at 4 p.m., we will say: welcome to "Leibniz-IWT live"!
Here, experienced employees of Leibniz-IWT report on their current research activities up to four times a year. Following the 30-minute lecture, the same amount of time is allotted for follow-up questions and lively discussion.
M.Sc. Bastian Lenz will give a presentation on the topic "Application of deep learning image recognition techniques for characterization of thin coatings".

For more than a year now, scientific congresses, trade fairs and discussion forums have had to be cancelled or moved to a restrictive digital format due to the pandemic. In order to reinvigorate regular exchange within materials, process and manufacturing engineering and to highlight current research topics, Leibniz-IWT is now setting up a new, free online format: "Leibniz-IWT live".

Here, experienced employees of Leibniz-IWT report on their current research activities up to four times a year. Following the 30-minute lecture, the same amount of time is allotted for follow-up questions and lively discussion, in which everyone is cordially invited to participate. The new lecture series is aimed at all interested parties from science and practice, regardless of whether they are already familiar with the IWT or are just getting to know it. The four annual lectures in this series of events cover a wide range of topics and projects and demonstrate the breadth of materials-oriented research.

For the last time this year, on December 2nd at 4 p.m., we will say: welcome to "Leibniz-IWT live"! And we are looking forward to seeing you again there.
Bastian Lenz will give a presentation on the topic "Application of deep learning image recognition techniques for characterization of thin coatings".
The presentation will again be digital via Webex.

Characterization methods are an important part of surface engineering and coating development. By using deep learning image classification and object detection techniques, some of them can be automatized to meet the latest digitalization demands.

The Rockwell-C and the Scratch-test are established methods for coating adhesion determination. Since they are based on the classification of light microscopic images, it is possible to substitute humans with trained special neuronal networks, the convolutional neural networks. These so-called CNN's are already being used successfully in a variety of other applications, and can be adapted for material science purposes.

As an extension of Vickers hardness testing, the Palmqvist method utilises crack formation at the edges of Vickers indentations to evaluate the fracture toughness of bulk materials and coatings. By using CNN-based object detection, the necessary indentation and crack size measurement can be automatized.

Information on participating / attending:
registration needed

Date:

12/02/2021 16:00 - 12/02/2021 17:00

Event venue:

online
online
Bremen
Germany

Target group:

Scientists and scholars, Students

Email address:

Relevance:

international

Subject areas:

Materials sciences, Mechanical engineering

Types of events:

Presentation / colloquium / lecture

Entry:

12/01/2021

Sender/author:

Belinda Schicks

Department:

Wissenschaftskommunikation

Event is free:

yes

Language of the text:

English

URL of this event: http://idw-online.de/en/event70327

Attachment
attachment icon Leibniz-IWT live logo

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