FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4378895678> ?p ?o ?g. }

• W4378895678 abstract "To address the low-efficiency issue of the manual assessment method for sewer pipe defects, we propose a defect severity assessment model based on automated pipe calibration (DSA-APC), which can provide automated and quantitative assessments. First, the cross-section feature is extracted by automated pipe calibration. A pipe cross-section feature extraction algorithm based on restricted Hough gradient transform (RHGT) is proposed. Then, a fine-defect feature extraction method based on edge detection is proposed to extract the features of pipe defects more finely. Finally, according to the assessment standards of the sewer pipe defect, a defect severity assessment table is constructed, and the area ratio of the defect feature and cross-section feature is used to evaluate the severity. Experiments are carried out on the Songbai data set and Level-sewer10 data set. The average absolute deviation of the DSA-APC model is 2.008%, and the average accuracy is 86.73%. The experimental results show that the DSA-APC model can correctly evaluate the severity level of sewer pipe defects, which has a good practical application value." @default.
• W4378895678 created "2023-06-01" @default.
• W4378895678 creator A5004148018 @default.
• W4378895678 creator A5025239624 @default.
• W4378895678 creator A5069939450 @default.
• W4378895678 creator A5086729425 @default.
• W4378895678 creator A5090546750 @default.
• W4378895678 date "2023-08-01" @default.
• W4378895678 modified "2023-09-25" @default.
• W4378895678 title "Defect Severity Assessment Model for Sewer Pipeline Based on Automated Pipe Calibration" @default.
• W4378895678 cites W1981387128 @default.
• W4378895678 cites W2009434431 @default.
• W4378895678 cites W2012444155 @default.
• W4378895678 cites W2029895480 @default.
• W4378895678 cites W2039183981 @default.
• W4378895678 cites W2065429801 @default.
• W4378895678 cites W2069999423 @default.
• W4378895678 cites W2085477122 @default.
• W4378895678 cites W2086991944 @default.
• W4378895678 cites W2091614835 @default.
• W4378895678 cites W2095905764 @default.
• W4378895678 cites W2139212933 @default.
• W4378895678 cites W2145023731 @default.
• W4378895678 cites W2164944168 @default.
• W4378895678 cites W22745672 @default.
• W4378895678 cites W2560622558 @default.
• W4378895678 cites W2588463901 @default.
• W4378895678 cites W2623211171 @default.
• W4378895678 cites W2788686737 @default.
• W4378895678 cites W2889035772 @default.
• W4378895678 cites W2912183379 @default.
• W4378895678 cites W2913697492 @default.
• W4378895678 cites W2916429473 @default.
• W4378895678 cites W2982168448 @default.
• W4378895678 cites W2982284503 @default.
• W4378895678 cites W2982512126 @default.
• W4378895678 cites W3023211159 @default.
• W4378895678 cites W3037064601 @default.
• W4378895678 cites W3093478663 @default.
• W4378895678 cites W3111544845 @default.
• W4378895678 cites W3111788780 @default.
• W4378895678 cites W3113175120 @default.
• W4378895678 cites W3125930480 @default.
• W4378895678 cites W3134535149 @default.
• W4378895678 cites W3156758967 @default.
• W4378895678 cites W4205371734 @default.
• W4378895678 cites W4213194009 @default.
• W4378895678 cites W4220700998 @default.
• W4378895678 cites W4220978806 @default.
• W4378895678 cites W4223425133 @default.
• W4378895678 cites W4225793543 @default.
• W4378895678 cites W4281993789 @default.
• W4378895678 cites W845365781 @default.
• W4378895678 doi "https://doi.org/10.1061/jpsea2.pseng-1454" @default.
• W4378895678 hasPublicationYear "2023" @default.
• W4378895678 type Work @default.
• W4378895678 citedByCount "0" @default.
• W4378895678 crossrefType "journal-article" @default.
• W4378895678 hasAuthorship W4378895678A5004148018 @default.
• W4378895678 hasAuthorship W4378895678A5025239624 @default.
• W4378895678 hasAuthorship W4378895678A5069939450 @default.
• W4378895678 hasAuthorship W4378895678A5086729425 @default.
• W4378895678 hasAuthorship W4378895678A5090546750 @default.
• W4378895678 hasConcept C105795698 @default.
• W4378895678 hasConcept C115961682 @default.
• W4378895678 hasConcept C124101348 @default.
• W4378895678 hasConcept C127413603 @default.
• W4378895678 hasConcept C138885662 @default.
• W4378895678 hasConcept C153180895 @default.
• W4378895678 hasConcept C154945302 @default.
• W4378895678 hasConcept C165838908 @default.
• W4378895678 hasConcept C175309249 @default.
• W4378895678 hasConcept C177264268 @default.
• W4378895678 hasConcept C199360897 @default.
• W4378895678 hasConcept C200518788 @default.
• W4378895678 hasConcept C2776401178 @default.
• W4378895678 hasConcept C33923547 @default.
• W4378895678 hasConcept C41008148 @default.
• W4378895678 hasConcept C41895202 @default.
• W4378895678 hasConcept C43521106 @default.
• W4378895678 hasConcept C52622490 @default.
• W4378895678 hasConcept C66938386 @default.
• W4378895678 hasConcept C87717796 @default.
• W4378895678 hasConceptScore W4378895678C105795698 @default.
• W4378895678 hasConceptScore W4378895678C115961682 @default.
• W4378895678 hasConceptScore W4378895678C124101348 @default.
• W4378895678 hasConceptScore W4378895678C127413603 @default.
• W4378895678 hasConceptScore W4378895678C138885662 @default.
• W4378895678 hasConceptScore W4378895678C153180895 @default.
• W4378895678 hasConceptScore W4378895678C154945302 @default.
• W4378895678 hasConceptScore W4378895678C165838908 @default.
• W4378895678 hasConceptScore W4378895678C175309249 @default.
• W4378895678 hasConceptScore W4378895678C177264268 @default.
• W4378895678 hasConceptScore W4378895678C199360897 @default.
• W4378895678 hasConceptScore W4378895678C200518788 @default.
• W4378895678 hasConceptScore W4378895678C2776401178 @default.
• W4378895678 hasConceptScore W4378895678C33923547 @default.
• W4378895678 hasConceptScore W4378895678C41008148 @default.
• W4378895678 hasConceptScore W4378895678C41895202 @default.
• W4378895678 hasConceptScore W4378895678C43521106 @default.

• next