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1.发明授权公开(公告)号：US10719720B2
公开(公告)日：2020-07-21
申请号：US16179021
申请日：2018-11-02
Inventor： Seung Ki Ryu
Abstract: Provided is an artificial intelligence system for providing road risk information and a method thereof. The system for providing road risk information includes: an information collection unit for receiving various road state information acquired from a vehicle device; an information processing unit for performing image processing on the collected road state information, and converting a result of the image processing into a predefined grayscale image; an information learning unit for learning the converted predefined grayscale image on the basis of a predetermined learning model based on deep learning, and recognizing the road risk information on the basis of a result of the learning; and an information classification unit for classifying the road risk information from the road state information on the basis of a result of the recognition, and detecting road surface defects on the basis of a result of the classification.
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公开(公告)号：US12293573B2
公开(公告)日：2025-05-06
申请号：US17991908
申请日：2022-11-22
Inventor： Seung Ki Ryu , Yeo Hwan Yoon , Young Seok Kim
IPC: G06V10/774
Abstract: The present invention relates to an apparatus and method for generating learning data for an artificial intelligence model, which generate learning data for learning of an artificial intelligence model that detects anomalies of a plant facility, and the apparatus and method collect at least one among structured data and unstructured data, and generate a learning data set for learning of an artificial intelligence model that predicts and diagnoses anomalies of a plant facility using at least one among the structured data and the unstructured data.
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3.发明申请公开(公告)号：US20190188501A1
公开(公告)日：2019-06-20
申请号：US16179021
申请日：2018-11-02
Inventor： Seung Ki Ryu
CPC classification number: G06K9/00805 , G06K9/6262 , G06K9/6267
Abstract: Provided is an artificial intelligence system for providing road risk information and a method thereof. The system for providing road risk information includes: an information collection unit for receiving various road state information acquired from a vehicle device; an information processing unit for performing image processing on the collected road state information, and converting a result of the image processing into a predefined grayscale image; an information learning unit for learning the converted predefined grayscale image on the basis of a predetermined learning model based on deep learning, and recognizing the road risk information on the basis of a result of the learning; and an information classification unit for classifying the road risk information from the road state information on the basis of a result of the recognition, and detecting road surface defects on the basis of a result of the classification.
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