Characterization of Magnetic Labyrinthine Structures Through Junctions and Terminals Detection Using Template Matching and CNN

Defects influence diverse properties of materials, shaping their structural, mechanical, and electronic characteristics. Among a variety of materials exhibiting unique defects, magnets exhibit diverse nano- to micro-scale defects and have been intensively studied in materials science. Specifically,...

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Veröffentlicht in:	IEEE access 2024, Vol.12, p.92419-92430
Hauptverfasser:	Okubo, Vinicius Yu, Shimizu, Kotaro, Shivaram, B. S., Yong Kim, Hae
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Annotations Artificial neural networks Computer vision Convolutional neural networks Deep learning Defects Feature extraction Junctions Magnetic domains magnetic labyrinthine patterns Magnetic materials Magnetic properties Magnetic resonance imaging Magnetic tunneling Magnets Material properties material science Materials science Materials science and technology Mechanical properties Neural networks object detection Object recognition Saturation magnetization Structural analysis Template matching
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