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- W2907888975 abstract "This paper considers a problem of understanding deformation motion of colloidal nanosheets from a set of confocal laser scanning microscopy (CLSM) images corrupted by noises. First, we present a robust method for detecting nanosheet objects from noisy CLSM images by introducing the deep learning-based approach. Then, we develop a method for understanding motions of nanosheet objects in colloid liquid. Such a method is constituted by introducing the idea of the so-called gradient-based feature descriptor, in which the local and global deformation motions are effectively visualized. The performance is demonstrated by some experimental studies." @default.
- W2907888975 created "2019-01-11" @default.
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- W2907888975 date "2018-11-01" @default.
- W2907888975 modified "2023-09-26" @default.
- W2907888975 title "Understanding Deformation Motion of Colloidal Nanosheets from CLSM Images using Deep Learning-based Approach" @default.
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- W2907888975 doi "https://doi.org/10.1109/icarcv.2018.8581084" @default.
- W2907888975 hasPublicationYear "2018" @default.
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