Evidence map›Paper›PMID 35161074›Full record

ArticleMaterials (Basel, Switzerland)2022

The Object Segmentation from the Microstructure of a FSW Dissimilar Weld.

Anna Wójcicka, Łukasz Walusiak, Krzysztof Mroczka, Joanna Krystyna Jaworek-Korjakowska, Krzysztof Oprzędkiewicz, Zygmunt Wrobel

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Anna WójcickaDepartment of Automatic Control and Robotics, AGH University of Science and Technology, 30-059 Cracow, Poland.
Łukasz WalusiakFaculty of Architecture, Civil Engineering and Applied Arts, University of Technology, Rolna 43, 40-555 Katowice, Poland.ORCID 0000-0002-9849-9764
Krzysztof MroczkaFaculty of Materials Engineering and Physics, Cracow University of Technology, 31-864 Cracow, Poland.
Joanna Krystyna Jaworek-KorjakowskaDepartment of Automatic Control and Robotics, AGH University of Science and Technology, 30-059 Cracow, Poland.ORCID 0000-0003-0146-8652
Krzysztof OprzędkiewiczDepartment of Automatic Control and Robotics, AGH University of Science and Technology, 30-059 Cracow, Poland.ORCID 0000-0002-8162-0011
Zygmunt WrobelInstitute of Biomedical Engineering, Faculty of Science and Technology, University of Silesia in Katowice, 41-205 Sosnowiec, Poland.

Funding

AGH University of Science and Technology xx
6 · The paper itself

Abstract

Friction stir welding (FSW) is an environmentally friendly, solid-state welding technique. In this research work, we analyze the microstructure of a new type of FSW weld applying a two- stage framework based on image processing algorithms containing a segmentation step and microstructure analysis of objects occurring in different layers. A dual-speed tool as used to prepare the tested weld. In this paper, we present the segmentation method for recognizing areas containing particles forming bands in the microstructure of a dissimilar weld of aluminum alloys made by FSW technology. A digital analysis was performed on the images obtained using an Olympus GX51 light microscope. The image analysis process consisted of basic segmentation methods in conjunction with domain knowledge and object detection located in different layers of a weld using morphological operations and point transformations. These methods proved to be effective in the analysis of the microstructure images corrupted by noise. The segmentation parts as well as single objects were separated enough to analyze the distribution on different layers of the specimen and the variability of shape and size of the underlying microstructures, which was not possible without computer vision support.

Indexed as

computer visiondual-speed toolFSWimage processingmicrostructure analysissegmentation

Identifiers

PMID35161074
PMCPMC8839914

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.