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http://thuvienso.vanlanguni.edu.vn/handle/Vanlang_TV/18412
Toàn bộ biểu ghi siêu dữ liệu
Trường DC | Giá trị | Ngôn ngữ |
---|---|---|
dc.contributor.author | Hoang, Nhat-Duc | - |
dc.date.accessioned | 2020-05-29T02:27:20Z | - |
dc.date.available | 2020-05-29T02:27:20Z | - |
dc.date.issued | 2018 | - |
dc.identifier.issn | 1687 - 8086 | - |
dc.identifier.other | BBKH1051 | - |
dc.identifier.uri | http://thuvienso.vanlanguni.edu.vn/handle/Vanlang_TV/18412 | - |
dc.description | "Hindawi Advances in Civil Engineering Volume 2018, Article ID 7419058, 12 pages https://doi.org/10.1155/2018/7419058" | vi |
dc.description.abstract | This study establishes an artificial intelligence (AI) model for detecting pothole on asphalt pavement surface. Image processing methods including Gaussian filter, steerable filter, and integral projection are utilized for extracting features from digital images. A data set consisting of 200 image samples has been collected to train and validate the predictive performance of two machine learning algorithms including the least squares support vector machine (LS-SVM) and the artificial neural network (ANN). Experimental results obtained from a repeated subsampling process with 20 runs show that both LS-SVM and ANN are capable methods for pothole detection with classification accuracy rate larger than 85%. In addition, the LS-SVM has achieved the highest classification accuracy rate (roughly 89%) and the area under the curve (0.96). Accordingly, the proposed AI approach used with LS-SVM can be very potential to assist transportation agencies and road inspectors in the task of pavement pothole detection. | vi |
dc.language.iso | en | vi |
dc.publisher | Hindawi Limited | vi |
dc.subject | Feature extraction | vi |
dc.subject | Digital imaging | vi |
dc.subject | Classification | vi |
dc.subject | Defects | vi |
dc.subject | Wavelet transforms | vi |
dc.subject | Performance prediction | vi |
dc.subject | Discriminant analysis | vi |
dc.subject | Artificial intelligence | vi |
dc.subject | Artificial neural networks | vi |
dc.title | An Artificial Intelligence Method for Asphalt Pavement Pothole Detection Using Least Squares Support Vector Machine and Neural Network with Steerable Filter-Based Feature Extraction | vi |
dc.type | Other | vi |
Bộ sưu tập: | Bài báo_lưu trữ |
Các tập tin trong tài liệu này:
Tập tin | Mô tả | Kích thước | Định dạng | |
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BBKH1051_TCCN_ An Artificial Intelligence.pdf Giới hạn truy cập | An Artificial Intelligence Method for Asphalt Pavement Pothole Detection Using Least Squares Support Vector Machine and Neural Network with Steerable Filter-Based Feature Extraction | 2.24 MB | Adobe PDF | Xem/Tải về Yêu cầu tài liệu |
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