Matches in SemOpenAlex for { <https://semopenalex.org/work/W3182494832> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W3182494832 endingPage "6292" @default.
- W3182494832 startingPage "6292" @default.
- W3182494832 abstract "In this study, we have proposed an algorithm that solves the problems which occur during the recognition of a vehicle license plate through closed-circuit television (CCTV) by using a deep learning model trained with a general database. The deep learning model which is commonly used suffers with a disadvantage of low recognition rate in the tilted and low-resolution images, as it is trained with images acquired from the front of the license plate. Furthermore, the vehicle images acquired by using CCTV have issues such as limitation of resolution and perspective distortion. Such factors make it difficult to apply the commonly used deep learning model. To improve the recognition rate, an algorithm which is a combination of the super-resolution generative adversarial network (SRGAN) model, and the perspective distortion correction algorithm is proposed in this paper. The accuracy of the proposed algorithm was verified with a character recognition algorithm YOLO v2, and the recognition rate of the vehicle license plate image was improved 8.8% from the original images." @default.
- W3182494832 created "2021-07-19" @default.
- W3182494832 creator A5011484641 @default.
- W3182494832 creator A5018641732 @default.
- W3182494832 creator A5019217862 @default.
- W3182494832 creator A5043731787 @default.
- W3182494832 creator A5049115494 @default.
- W3182494832 creator A5060425240 @default.
- W3182494832 creator A5066797325 @default.
- W3182494832 date "2021-07-07" @default.
- W3182494832 modified "2023-09-26" @default.
- W3182494832 title "Recognition of Vehicle License Plates Based on Image Processing" @default.
- W3182494832 cites W2001670255 @default.
- W3182494832 cites W2133059825 @default.
- W3182494832 cites W2135449683 @default.
- W3182494832 cites W2160921898 @default.
- W3182494832 cites W2543461915 @default.
- W3182494832 cites W2613449306 @default.
- W3182494832 cites W2800816754 @default.
- W3182494832 cites W2946147212 @default.
- W3182494832 cites W2967261838 @default.
- W3182494832 cites W2999630082 @default.
- W3182494832 cites W3017825328 @default.
- W3182494832 cites W3022690034 @default.
- W3182494832 cites W3048468555 @default.
- W3182494832 cites W3128685005 @default.
- W3182494832 cites W3154203438 @default.
- W3182494832 doi "https://doi.org/10.3390/app11146292" @default.
- W3182494832 hasPublicationYear "2021" @default.
- W3182494832 type Work @default.
- W3182494832 sameAs 3182494832 @default.
- W3182494832 citedByCount "9" @default.
- W3182494832 countsByYear W31824948322022 @default.
- W3182494832 countsByYear W31824948322023 @default.
- W3182494832 crossrefType "journal-article" @default.
- W3182494832 hasAuthorship W3182494832A5011484641 @default.
- W3182494832 hasAuthorship W3182494832A5018641732 @default.
- W3182494832 hasAuthorship W3182494832A5019217862 @default.
- W3182494832 hasAuthorship W3182494832A5043731787 @default.
- W3182494832 hasAuthorship W3182494832A5049115494 @default.
- W3182494832 hasAuthorship W3182494832A5060425240 @default.
- W3182494832 hasAuthorship W3182494832A5066797325 @default.
- W3182494832 hasBestOaLocation W31824948321 @default.
- W3182494832 hasConcept C108583219 @default.
- W3182494832 hasConcept C111919701 @default.
- W3182494832 hasConcept C115961682 @default.
- W3182494832 hasConcept C126780896 @default.
- W3182494832 hasConcept C12713177 @default.
- W3182494832 hasConcept C153180895 @default.
- W3182494832 hasConcept C154945302 @default.
- W3182494832 hasConcept C194257627 @default.
- W3182494832 hasConcept C2776257435 @default.
- W3182494832 hasConcept C2780560020 @default.
- W3182494832 hasConcept C31258907 @default.
- W3182494832 hasConcept C31972630 @default.
- W3182494832 hasConcept C41008148 @default.
- W3182494832 hasConceptScore W3182494832C108583219 @default.
- W3182494832 hasConceptScore W3182494832C111919701 @default.
- W3182494832 hasConceptScore W3182494832C115961682 @default.
- W3182494832 hasConceptScore W3182494832C126780896 @default.
- W3182494832 hasConceptScore W3182494832C12713177 @default.
- W3182494832 hasConceptScore W3182494832C153180895 @default.
- W3182494832 hasConceptScore W3182494832C154945302 @default.
- W3182494832 hasConceptScore W3182494832C194257627 @default.
- W3182494832 hasConceptScore W3182494832C2776257435 @default.
- W3182494832 hasConceptScore W3182494832C2780560020 @default.
- W3182494832 hasConceptScore W3182494832C31258907 @default.
- W3182494832 hasConceptScore W3182494832C31972630 @default.
- W3182494832 hasConceptScore W3182494832C41008148 @default.
- W3182494832 hasIssue "14" @default.
- W3182494832 hasLocation W31824948321 @default.
- W3182494832 hasLocation W31824948322 @default.
- W3182494832 hasOpenAccess W3182494832 @default.
- W3182494832 hasPrimaryLocation W31824948321 @default.
- W3182494832 hasRelatedWork W2033534994 @default.
- W3182494832 hasRelatedWork W2080322084 @default.
- W3182494832 hasRelatedWork W2116241442 @default.
- W3182494832 hasRelatedWork W2130228941 @default.
- W3182494832 hasRelatedWork W2161229648 @default.
- W3182494832 hasRelatedWork W2167335035 @default.
- W3182494832 hasRelatedWork W2414946225 @default.
- W3182494832 hasRelatedWork W2738221750 @default.
- W3182494832 hasRelatedWork W2993674027 @default.
- W3182494832 hasRelatedWork W2541128885 @default.
- W3182494832 hasVolume "11" @default.
- W3182494832 isParatext "false" @default.
- W3182494832 isRetracted "false" @default.
- W3182494832 magId "3182494832" @default.
- W3182494832 workType "article" @default.