Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387515118> ?p ?o ?g. }
- W4387515118 endingPage "103510" @default.
- W4387515118 startingPage "103510" @default.
- W4387515118 abstract "The acceleration of urbanization and the increasing demand for precise city planning have made the extraction of buildings and roads from remote sensing images crucial. Deep learning-based methods have propelled the progress of object extraction technology, but there are still challenges such as the missing and incomplete extraction of buildings and roads for small objects and occlusions. To address this issue, we propose a dual-path extraction network based on CNN and Transformer, combining local and global features to fully extract the semantic information of objects. To further enhance the semantic reconstruction capability of features, this paper introduces a multi-scale upsampling mechanism, thereby expanding the visual range of reconstruction. Finally, we adopt a deep supervision strategy to improve the reconstruction accuracy of objects at different resolutions. Our method has been tested on four remote sensing image datasets and has achieved excellent IoU scores on all datasets (Massachusetts Building and Roads Dataset: 76.69% and 66.41%, LRSNY and CHN6-CUG Roads Dataset: 88.96% and 61.99%). Furthermore, our method demonstrates superior performance compared to other mainstream image segmentation algorithms, fully demonstrating the effectiveness of our approach." @default.
- W4387515118 created "2023-10-11" @default.
- W4387515118 creator A5007144110 @default.
- W4387515118 creator A5018474596 @default.
- W4387515118 creator A5026327136 @default.
- W4387515118 creator A5055805718 @default.
- W4387515118 creator A5068910752 @default.
- W4387515118 creator A5070945206 @default.
- W4387515118 date "2023-11-01" @default.
- W4387515118 modified "2023-10-12" @default.
- W4387515118 title "DPENet: Dual-path extraction network based on CNN and transformer for accurate building and road extraction" @default.
- W4387515118 cites W1901129140 @default.
- W4387515118 cites W2560023338 @default.
- W4387515118 cites W2774320778 @default.
- W4387515118 cites W2787614951 @default.
- W4387515118 cites W2939647427 @default.
- W4387515118 cites W2955058313 @default.
- W4387515118 cites W2963881378 @default.
- W4387515118 cites W2964309882 @default.
- W4387515118 cites W2982206001 @default.
- W4387515118 cites W2992559558 @default.
- W4387515118 cites W3011990881 @default.
- W4387515118 cites W3014060899 @default.
- W4387515118 cites W3018914855 @default.
- W4387515118 cites W3022397457 @default.
- W4387515118 cites W3024167159 @default.
- W4387515118 cites W3025172026 @default.
- W4387515118 cites W3035012694 @default.
- W4387515118 cites W3047725879 @default.
- W4387515118 cites W3081791696 @default.
- W4387515118 cites W3111982977 @default.
- W4387515118 cites W3121754326 @default.
- W4387515118 cites W3126435384 @default.
- W4387515118 cites W3143901569 @default.
- W4387515118 cites W3150573203 @default.
- W4387515118 cites W3174867596 @default.
- W4387515118 cites W3175430845 @default.
- W4387515118 cites W3176363936 @default.
- W4387515118 cites W3187079290 @default.
- W4387515118 cites W3211146446 @default.
- W4387515118 cites W3211329537 @default.
- W4387515118 cites W3217005392 @default.
- W4387515118 cites W4210427448 @default.
- W4387515118 cites W4226378839 @default.
- W4387515118 cites W4296830112 @default.
- W4387515118 cites W4297478639 @default.
- W4387515118 cites W4307623804 @default.
- W4387515118 cites W4320919181 @default.
- W4387515118 cites W4321232185 @default.
- W4387515118 cites W4327620107 @default.
- W4387515118 cites W4327695706 @default.
- W4387515118 doi "https://doi.org/10.1016/j.jag.2023.103510" @default.
- W4387515118 hasPublicationYear "2023" @default.
- W4387515118 type Work @default.
- W4387515118 citedByCount "0" @default.
- W4387515118 crossrefType "journal-article" @default.
- W4387515118 hasAuthorship W4387515118A5007144110 @default.
- W4387515118 hasAuthorship W4387515118A5018474596 @default.
- W4387515118 hasAuthorship W4387515118A5026327136 @default.
- W4387515118 hasAuthorship W4387515118A5055805718 @default.
- W4387515118 hasAuthorship W4387515118A5068910752 @default.
- W4387515118 hasAuthorship W4387515118A5070945206 @default.
- W4387515118 hasBestOaLocation W43875151181 @default.
- W4387515118 hasConcept C108583219 @default.
- W4387515118 hasConcept C110384440 @default.
- W4387515118 hasConcept C115961682 @default.
- W4387515118 hasConcept C119599485 @default.
- W4387515118 hasConcept C124101348 @default.
- W4387515118 hasConcept C127413603 @default.
- W4387515118 hasConcept C154945302 @default.
- W4387515118 hasConcept C165801399 @default.
- W4387515118 hasConcept C31972630 @default.
- W4387515118 hasConcept C41008148 @default.
- W4387515118 hasConcept C52622490 @default.
- W4387515118 hasConcept C66322947 @default.
- W4387515118 hasConcept C89600930 @default.
- W4387515118 hasConceptScore W4387515118C108583219 @default.
- W4387515118 hasConceptScore W4387515118C110384440 @default.
- W4387515118 hasConceptScore W4387515118C115961682 @default.
- W4387515118 hasConceptScore W4387515118C119599485 @default.
- W4387515118 hasConceptScore W4387515118C124101348 @default.
- W4387515118 hasConceptScore W4387515118C127413603 @default.
- W4387515118 hasConceptScore W4387515118C154945302 @default.
- W4387515118 hasConceptScore W4387515118C165801399 @default.
- W4387515118 hasConceptScore W4387515118C31972630 @default.
- W4387515118 hasConceptScore W4387515118C41008148 @default.
- W4387515118 hasConceptScore W4387515118C52622490 @default.
- W4387515118 hasConceptScore W4387515118C66322947 @default.
- W4387515118 hasConceptScore W4387515118C89600930 @default.
- W4387515118 hasLocation W43875151181 @default.
- W4387515118 hasOpenAccess W4387515118 @default.
- W4387515118 hasPrimaryLocation W43875151181 @default.
- W4387515118 hasRelatedWork W1983892167 @default.
- W4387515118 hasRelatedWork W1991429770 @default.
- W4387515118 hasRelatedWork W2281134365 @default.
- W4387515118 hasRelatedWork W2607795551 @default.
- W4387515118 hasRelatedWork W3155117723 @default.
- W4387515118 hasRelatedWork W4212888438 @default.