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Showing 201 - 220 results of 2,712 for search 'materials image processing', query time: 0.18s Refine Results
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    TXM-Pal: a companion software for advanced data processing in spectroscopic X-ray microscopy by Sugeun Jo, Sangwoo Kim, Jun Lim

    Published 2025-05-01
    “…This software includes a user-friendly graphical user interface that facilitates XANES analysis, allowing images to be processed within a few minutes. The Rust-based implementation in TXM-Pal accelerates data analysis by tens of times compared with programs of pure Python. …”
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    Computational approaches for structural analysis of wood specimens by Chakkour Tarik

    Published 2024-12-01
    “…The structure tensor (ST), also named a second-moment matrix, is a popular tool in image processing. Usually, its purpose is to evaluate orientation and to conduct local structural analysis. …”
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  7. 207

    Real-Time Stringing Detection for Additive Manufacturing by Oumaima Charia, Hayat Rajani, Inés Ferrer Real, Miquel Domingo-Espin, Nuno Gracias

    Published 2025-02-01
    “…Such errors often go undetected for extended periods, resulting in substantial losses of time and material. This study explores the implementation of traditional computer vision, image processing, and machine learning techniques to enable real-time error detection, specifically focusing on stringing-related anomalies. …”
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    Phase formation and texture evolution in 316L-CuCrZr multi-material structures fabricated by laser powder bed fusion by Antonios Baganis, Florencia Malamud, Jan Čapek, Fedor F. Klimashin, Efthymios Polatidis, Matteo Busi, Miroslav Šmíd, Michal Jambor, Johann Michler, Markus Strobl, Christian Leinenbach

    Published 2025-08-01
    “…Steel-copper multi-material structures produced via Additive Manufacturing pose challenges in laser co-processing and microstructural control. …”
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    Determining the optimal choice of attenuation filters and propagation distance for polychromatic phase-contrast micro-computed tomography of a multi-material electromotor using syn... by Matthias Diez, Simon Zabler

    Published 2025-05-01
    “…A physically accurate model of the complete imaging process may not only allow for optimization by simulation but also ideally improve CT image reconstruction in the near future.…”
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    Unravel melt pool and bubble dynamics during laser powder bed fusion of polyamides using synchrotron X-ray imaging and process simulation by Chu Lun Alex Leung, Jabbar Gardy, Mark Isaacs, Shashidhara Marathe, Michał M. Kłosowski, Junji Shinjo, Chinnapat Panwisawas, Peter D. Lee

    Published 2025-12-01
    “…Here, we employed a combination of in situ synchrotron X-ray imaging, ex situ materials characterisation techniques, and high-fidelity process simulations to study these behaviours during LPBF of PA12. …”
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    A feasibility Study of Detecting Chironomidae Larva in Water Treatment Filtration Processes using ResNet-based Image Recognition Deep Learning by Si Hyeong Park, Myeong Eon Choi, Seung Yong Lee, Jong-Oh Kim, No-Suk Park

    Published 2025-05-01
    “…This study was conducted to determine whether the presence or absence of larva that may appear in filters through image data analysis. Image data were created for cases with and without larva background with interference materials such as sand and activated carbon granules used in the actual water treatment process. …”
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    Application of satellite images and object-oriented processing in land use/land cover map extraction to model ecosystem services (case study: Lorestan province) by Zahra Asadolahi, Mostafa Keshtkar, Zia Badehian

    Published 2020-09-01
    “…Material and methods: The research was carried out using eCognition 9.01 and InVEST3.0 software in four steps including preparing information, object-oriented processing of satellite images, object-oriented classification, and finally, habitat modeling. …”
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    Autonomous defect estimation in aluminum plate and prognosis through stochastic process modeling by Mrudul Jambulkar, Shivam Ojha, Amit Shelke, Anowarul Habib

    Published 2025-08-01
    “…To overcome these challenges, this study proposes an unsupervised learning framework that combines k-means clustering with a multi-phase gamma process to detect and model damage in aluminum plates. …”
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