FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313259648> ?p ?o ?g. }

• W4313259648 endingPage "95" @default.
• W4313259648 startingPage "95" @default.
• W4313259648 abstract "Convolutional neural networks (CNNs) perform well in tasks of segmenting buildings from remote sensing images. However, the intraclass heterogeneity of buildings is high in images, while the interclass homogeneity between buildings and other nonbuilding objects is low. This leads to an inaccurate distinction between buildings and complex backgrounds. To overcome this challenge, we propose an Attentional Feature Learning Network (AFL-Net) that can accurately extract buildings from remote sensing images. We designed an attentional multiscale feature fusion (AMFF) module and a shape feature refinement (SFR) module to improve building recognition accuracy in complex environments. The AMFF module adaptively adjusts the weights of multi-scale features through the attention mechanism, which enhances the global perception and ensures the integrity of building segmentation results. The SFR module captures the shape features of the buildings, which enhances the network capability for identifying the area between building edges and surrounding nonbuilding objects and reduces the over-segmentation of buildings. An ablation study was conducted with both qualitative and quantitative analyses, verifying the effectiveness of the AMFF and SFR modules. The proposed AFL-Net achieved 91.37, 82.10, 73.27, and 79.81% intersection over union (IoU) values on the WHU Building Aerial Imagery, Inria Aerial Image Labeling, Massachusetts Buildings, and Building Instances of Typical Cities in China datasets, respectively. Thus, the AFL-Net offers the prospect of application for successful extraction of buildings from remote sensing images." @default.
• W4313259648 created "2023-01-06" @default.
• W4313259648 creator A5000153912 @default.
• W4313259648 creator A5024762618 @default.
• W4313259648 creator A5048461053 @default.
• W4313259648 creator A5052883222 @default.
• W4313259648 creator A5054332012 @default.
• W4313259648 creator A5073933345 @default.
• W4313259648 creator A5079099677 @default.
• W4313259648 creator A5081393853 @default.
• W4313259648 date "2022-12-24" @default.
• W4313259648 modified "2023-09-30" @default.
• W4313259648 title "AFL-Net: Attentional Feature Learning Network for Building Extraction from Remote Sensing Images" @default.
• W4313259648 cites W1901129140 @default.
• W4313259648 cites W1903029394 @default.
• W4313259648 cites W2045366687 @default.
• W4313259648 cites W2124641210 @default.
• W4313259648 cites W2412782625 @default.
• W4313259648 cites W2533566148 @default.
• W4313259648 cites W2565950292 @default.
• W4313259648 cites W2609402060 @default.
• W4313259648 cites W2623490820 @default.
• W4313259648 cites W2752782242 @default.
• W4313259648 cites W2794606897 @default.
• W4313259648 cites W2908320224 @default.
• W4313259648 cites W2909555159 @default.
• W4313259648 cites W2916798096 @default.
• W4313259648 cites W2963881378 @default.
• W4313259648 cites W2966926453 @default.
• W4313259648 cites W2982206001 @default.
• W4313259648 cites W2987361643 @default.
• W4313259648 cites W2990228562 @default.
• W4313259648 cites W3027225766 @default.
• W4313259648 cites W3096168491 @default.
• W4313259648 cites W3125885648 @default.
• W4313259648 cites W3126435384 @default.
• W4313259648 cites W3150573203 @default.
• W4313259648 cites W3168588044 @default.
• W4313259648 cites W3202128323 @default.
• W4313259648 cites W3211329537 @default.
• W4313259648 cites W3217745064 @default.
• W4313259648 cites W4206007731 @default.
• W4313259648 cites W4214760051 @default.
• W4313259648 cites W4224055292 @default.
• W4313259648 cites W4229441694 @default.
• W4313259648 cites W4239999461 @default.
• W4313259648 cites W4281396110 @default.
• W4313259648 cites W4285070909 @default.
• W4313259648 cites W4285604868 @default.
• W4313259648 cites W4291913402 @default.
• W4313259648 cites W4296829473 @default.
• W4313259648 doi "https://doi.org/10.3390/rs15010095" @default.
• W4313259648 hasPublicationYear "2022" @default.
• W4313259648 type Work @default.
• W4313259648 citedByCount "0" @default.
• W4313259648 crossrefType "journal-article" @default.
• W4313259648 hasAuthorship W4313259648A5000153912 @default.
• W4313259648 hasAuthorship W4313259648A5024762618 @default.
• W4313259648 hasAuthorship W4313259648A5048461053 @default.
• W4313259648 hasAuthorship W4313259648A5052883222 @default.
• W4313259648 hasAuthorship W4313259648A5054332012 @default.
• W4313259648 hasAuthorship W4313259648A5073933345 @default.
• W4313259648 hasAuthorship W4313259648A5079099677 @default.
• W4313259648 hasAuthorship W4313259648A5081393853 @default.
• W4313259648 hasBestOaLocation W43132596481 @default.
• W4313259648 hasConcept C115961682 @default.
• W4313259648 hasConcept C138885662 @default.
• W4313259648 hasConcept C153180895 @default.
• W4313259648 hasConcept C154945302 @default.
• W4313259648 hasConcept C205649164 @default.
• W4313259648 hasConcept C2776401178 @default.
• W4313259648 hasConcept C2776429412 @default.
• W4313259648 hasConcept C2987819851 @default.
• W4313259648 hasConcept C31972630 @default.
• W4313259648 hasConcept C41008148 @default.
• W4313259648 hasConcept C41895202 @default.
• W4313259648 hasConcept C62649853 @default.
• W4313259648 hasConcept C81363708 @default.
• W4313259648 hasConcept C89600930 @default.
• W4313259648 hasConceptScore W4313259648C115961682 @default.
• W4313259648 hasConceptScore W4313259648C138885662 @default.
• W4313259648 hasConceptScore W4313259648C153180895 @default.
• W4313259648 hasConceptScore W4313259648C154945302 @default.
• W4313259648 hasConceptScore W4313259648C205649164 @default.
• W4313259648 hasConceptScore W4313259648C2776401178 @default.
• W4313259648 hasConceptScore W4313259648C2776429412 @default.
• W4313259648 hasConceptScore W4313259648C2987819851 @default.
• W4313259648 hasConceptScore W4313259648C31972630 @default.
• W4313259648 hasConceptScore W4313259648C41008148 @default.
• W4313259648 hasConceptScore W4313259648C41895202 @default.
• W4313259648 hasConceptScore W4313259648C62649853 @default.
• W4313259648 hasConceptScore W4313259648C81363708 @default.
• W4313259648 hasConceptScore W4313259648C89600930 @default.
• W4313259648 hasFunder F4320321001 @default.
• W4313259648 hasIssue "1" @default.
• W4313259648 hasLocation W43132596481 @default.
• W4313259648 hasLocation W43132596482 @default.
• W4313259648 hasOpenAccess W4313259648 @default.

• next