FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4280551717> ?p ?o ?g. }

• W4280551717 endingPage "14" @default.
• W4280551717 startingPage "1" @default.
• W4280551717 abstract "The clutter in the ground-penetrating radar (GPR) radargram disguises or distorts subsurface target responses, which severely affects the accuracy of target detection and identification. Existing clutter removal methods either leave residual clutter or deform target responses when facing complex and irregular clutter in the real-world radargram. To tackle the challenge of clutter removal in real scenarios, a clutter-removal neural network (CR-Net) trained on a large-scale hybrid dataset is presented in this study. The CR-Net integrates residual dense blocks into the U-Net architecture to enhance its capability in clutter suppression and target reflection restoration. The combination of the mean absolute error (MAE) loss and the multi-scale structural similarity (MS-SSIM) loss is used to effectively drive the optimization of the network. To train the proposed CR-Net to remove complex and diverse clutter in real-world radargrams, the first large-scale hybrid dataset named CLT-GPR dataset containing clutter collected by different GPR systems in multiple scenarios is built. The CLT-GPR dataset significantly improves the generalizability of the network to remove clutter in real-world GPR radargrams. Extensive experimental results demonstrate that the CR-Net achieves superior performance over existing methods in removing clutter and restoring target responses in diverse real-world scenarios. Moreover, the CR-Net with its end-to-end design does not require manual parameter tuning, making it highly suitable for automatically producing clutter-free radargrams in GPR applications. The CLT-GPR dataset and the code implemented in the paper can be found at https://haihan-sun.github.io/GPR.html." @default.
• W4280551717 created "2022-05-22" @default.
• W4280551717 creator A5033289076 @default.
• W4280551717 creator A5074943100 @default.
• W4280551717 creator A5082726444 @default.
• W4280551717 date "2022-01-01" @default.
• W4280551717 modified "2023-10-11" @default.
• W4280551717 title "Learning to Remove Clutter in Real-World GPR Images Using Hybrid Data" @default.
• W4280551717 cites W1580389772 @default.
• W4280551717 cites W1841379813 @default.
• W4280551717 cites W1879695671 @default.
• W4280551717 cites W1998239584 @default.
• W4280551717 cites W2056602210 @default.
• W4280551717 cites W2066218102 @default.
• W4280551717 cites W2080719777 @default.
• W4280551717 cites W2095432062 @default.
• W4280551717 cites W2097420428 @default.
• W4280551717 cites W2100369874 @default.
• W4280551717 cites W2101316886 @default.
• W4280551717 cites W2103261682 @default.
• W4280551717 cites W2107302051 @default.
• W4280551717 cites W2113638573 @default.
• W4280551717 cites W2123376510 @default.
• W4280551717 cites W2128131274 @default.
• W4280551717 cites W2129544209 @default.
• W4280551717 cites W2131730299 @default.
• W4280551717 cites W2142825035 @default.
• W4280551717 cites W2166743408 @default.
• W4280551717 cites W2169446348 @default.
• W4280551717 cites W2395626468 @default.
• W4280551717 cites W2518909974 @default.
• W4280551717 cites W2528186534 @default.
• W4280551717 cites W2562637781 @default.
• W4280551717 cites W2728294189 @default.
• W4280551717 cites W2794881565 @default.
• W4280551717 cites W2810458289 @default.
• W4280551717 cites W2888033104 @default.
• W4280551717 cites W2890647011 @default.
• W4280551717 cites W2893824312 @default.
• W4280551717 cites W2894120608 @default.
• W4280551717 cites W2901206390 @default.
• W4280551717 cites W2916798096 @default.
• W4280551717 cites W2964101377 @default.
• W4280551717 cites W2972774735 @default.
• W4280551717 cites W3012140695 @default.
• W4280551717 cites W3013741472 @default.
• W4280551717 cites W3029679819 @default.
• W4280551717 cites W3043111816 @default.
• W4280551717 cites W3044021650 @default.
• W4280551717 cites W3090178411 @default.
• W4280551717 cites W3121869276 @default.
• W4280551717 cites W3128897538 @default.
• W4280551717 cites W3149976863 @default.
• W4280551717 cites W3174465795 @default.
• W4280551717 cites W3185315065 @default.
• W4280551717 cites W3192901833 @default.
• W4280551717 cites W3203499233 @default.
• W4280551717 cites W4231826386 @default.
• W4280551717 cites W4241748932 @default.
• W4280551717 doi "https://doi.org/10.1109/tgrs.2022.3176029" @default.
• W4280551717 hasPublicationYear "2022" @default.
• W4280551717 type Work @default.
• W4280551717 citedByCount "12" @default.
• W4280551717 countsByYear W42805517172022 @default.
• W4280551717 countsByYear W42805517172023 @default.
• W4280551717 crossrefType "journal-article" @default.
• W4280551717 hasAuthorship W4280551717A5033289076 @default.
• W4280551717 hasAuthorship W4280551717A5074943100 @default.
• W4280551717 hasAuthorship W4280551717A5082726444 @default.
• W4280551717 hasBestOaLocation W42805517172 @default.
• W4280551717 hasConcept C11413529 @default.
• W4280551717 hasConcept C127313418 @default.
• W4280551717 hasConcept C132094186 @default.
• W4280551717 hasConcept C153180895 @default.
• W4280551717 hasConcept C154945302 @default.
• W4280551717 hasConcept C155512373 @default.
• W4280551717 hasConcept C41008148 @default.
• W4280551717 hasConcept C50644808 @default.
• W4280551717 hasConcept C554190296 @default.
• W4280551717 hasConcept C62649853 @default.
• W4280551717 hasConcept C71813955 @default.
• W4280551717 hasConcept C76155785 @default.
• W4280551717 hasConcept C77052588 @default.
• W4280551717 hasConceptScore W4280551717C11413529 @default.
• W4280551717 hasConceptScore W4280551717C127313418 @default.
• W4280551717 hasConceptScore W4280551717C132094186 @default.
• W4280551717 hasConceptScore W4280551717C153180895 @default.
• W4280551717 hasConceptScore W4280551717C154945302 @default.
• W4280551717 hasConceptScore W4280551717C155512373 @default.
• W4280551717 hasConceptScore W4280551717C41008148 @default.
• W4280551717 hasConceptScore W4280551717C50644808 @default.
• W4280551717 hasConceptScore W4280551717C554190296 @default.
• W4280551717 hasConceptScore W4280551717C62649853 @default.
• W4280551717 hasConceptScore W4280551717C71813955 @default.
• W4280551717 hasConceptScore W4280551717C76155785 @default.
• W4280551717 hasConceptScore W4280551717C77052588 @default.
• W4280551717 hasFunder F4320334971 @default.
• W4280551717 hasLocation W42805517171 @default.

• next