Yang et al., 2020 - Google Patents

Two-step surface damage detection scheme using convolutional neural network and artificial neural network

Yang et al., 2020

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Document ID
11793497558409816339
Author
Yang A
Cheng L
Publication year
Publication venue
2020 IEEE 23rd International Conference on Information Fusion (FUSION)

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Snippet

Surface damage on concrete is important as the damage can affect the structural integrity of the structure. This paper proposes a two-step surface damage detection scheme using Convolutional Neural Network (CNN) and Artificial Neural Network (ANN). The CNN …
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Classifications

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    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
    • G06K9/4609—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections by matching or filtering
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    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6228—Selecting the most significant subset of features
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    • G06K9/00597—Acquiring or recognising eyes, e.g. iris verification

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