Analysis of SEM Images with Artificial Intelligence Methods

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dc.contributor.authorDemirkan, Ayşe
dc.contributor.authorTopcu, İsmail
dc.date.accessioned2026-01-24T11:55:46Z
dc.date.available2026-01-24T11:55:46Z
dc.date.issued2022
dc.departmentAlanya Alaaddin Keykubat Üniversitesi
dc.description.abstractToday, the quality of Nanotechnology and Nanoscience working with Artificial Intelligence is increasing day by day. Gains the importance of materials science effectively. Examination of SEM Images with Artificial Intelligence Methods represents a multidisciplinary field. In forming the data used in the experimental part, 22,000 SEM data are publicly available. It is known that CNR-IOM's TASC laboratory in Trieste was obtained as a result of 5 years of work of 100 scientists with the ZEISS SUPRA 40 resolution device. After examining the resolution, image size and quality one by one for the selection of the data in the prototype created for the experimental study, the feature that is considered is the image quality. In the creation of this data, after 100 image data are manually selected and arranged in nano and micro dimensions; A total of 1000 image data were created in 10 data sets. Then, artificial intelligence training was carried out using the CNN classification technique in the experimental study using the unsupervised learning method through machine learning. The approach used here enables the application of new methods and tools by adjusting to develop suitable parameters to solve specific properties of nanomaterials that can be applied to a wide variety of nanoscience use cases. Using it to create a materials science library may pave the way for future studies in the field of artificial intelligence and nanotechnology.
dc.description.abstractToday, the quality of Nanotechnology and Nanoscience working with Artificial Intelligence is increasing day by day. Gains the importance of materials science effectively. Examination of SEM Images with Artificial Intelligence Methods represents a multidisciplinary field. In forming the data used in the experimental part, 22,000 SEM data are publicly available. It is known that CNR-IOM's TASC laboratory in Trieste was obtained as a result of 5 years of work of 100 scientists with the ZEISS SUPRA 40 resolution device. After examining the resolution, image size and quality one by one for the selection of the data in the prototype created for the experimental study, the feature that is considered is the image quality. In the creation of this data, after 100 image data are manually selected and arranged in nano and micro dimensions; A total of 1000 image data were created in 10 data sets. Then, artificial intelligence training was carried out using the CNN classification technique in the experimental study using the unsupervised learning method through machine learning. The approach used here enables the application of new methods and tools by adjusting to develop suitable parameters to solve specific properties of nanomaterials that can be applied to a wide variety of nanoscience use cases. Using it to create a materials science library may pave the way for future studies in the field of artificial intelligence and nanotechnology.
dc.identifier.doi10.31590/ejosat.1219252
dc.identifier.endpage38
dc.identifier.issn2148-2683
dc.identifier.issue44
dc.identifier.startpage35
dc.identifier.urihttps://doi.org/10.31590/ejosat.1219252
dc.identifier.urihttps://hdl.handle.net/20.500.12868/3235
dc.language.isoen
dc.publisherOsman SAĞDIÇ
dc.relation.ispartofEuropean Journal of Science and Technology
dc.relation.ispartofAvrupa Bilim ve Teknoloji Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20260121
dc.subjectEngineering
dc.subjectMühendislik
dc.titleAnalysis of SEM Images with Artificial Intelligence Methods
dc.title.alternativeAnalysis of SEM Images with Artificial Intelligence Methods
dc.typeArticle

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