FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3194808133> ?p ?o ?g. }

• W3194808133 endingPage "7894" @default.
• W3194808133 startingPage "7881" @default.
• W3194808133 abstract "The recognition and mapping of landslide (RML) is an important task in hazard and risk research and can provide a scientific basis for the prevention and control of landslide disasters. However, traditional RML methods are inefficient, costly, and not intuitive. With the rapid development of computer vision, methods based on convolutional neural networks have attracted great attention due to their numerous advantages. However, problems such as insufficient feature extraction, excessive parameters, and slow model testing have restricted the development of this technology. This research proposes a new RML framework based on a new semantic segmentation network termed the fully convolutional DenseNet (FC-DenseNet). In this network, the features extracted from each layer are repeatedly used in a dense connection, and the parameters are controlled by a bottle-neck structure. Meanwhile, the structure of the encoder-decoder solves the problem of the slowness of model testing. Finally, the landslide influencing factors are added, which enriches the training data. To verify the effectiveness of the proposed method, we focused on several deep networks for comparison and analysis. The results show that FC-DenseNet can better recognize the boundary and interior of landslides, and there are fewer missing and excessive recognition results. The kappa value of the new method is 94.72% in Site 1, which is 6% and 4% higher than that of U-Net and ResU-Net, respectively, and 94.56% in Site 2, which is 6% and 3% higher than that of U-Net and ResU-Net, respectively, indicating that FC-DenseNet has great potential in RML applications." @default.
• W3194808133 created "2021-08-30" @default.
• W3194808133 creator A5054292278 @default.
• W3194808133 creator A5063163226 @default.
• W3194808133 creator A5063406632 @default.
• W3194808133 creator A5084606868 @default.
• W3194808133 date "2021-01-01" @default.
• W3194808133 modified "2023-10-17" @default.
• W3194808133 title "Recognition and Mapping of Landslide Using a Fully Convolutional DenseNet and Influencing Factors" @default.
• W3194808133 cites W1012081417 @default.
• W3194808133 cites W1901129140 @default.
• W3194808133 cites W1903029394 @default.
• W3194808133 cites W2005948635 @default.
• W3194808133 cites W2012089683 @default.
• W3194808133 cites W2016016500 @default.
• W3194808133 cites W2053536071 @default.
• W3194808133 cites W2058082754 @default.
• W3194808133 cites W2063987149 @default.
• W3194808133 cites W2093650457 @default.
• W3194808133 cites W2095057310 @default.
• W3194808133 cites W2097117768 @default.
• W3194808133 cites W2112796928 @default.
• W3194808133 cites W2155789665 @default.
• W3194808133 cites W2194775991 @default.
• W3194808133 cites W2236234032 @default.
• W3194808133 cites W2322428454 @default.
• W3194808133 cites W2333375380 @default.
• W3194808133 cites W2414813772 @default.
• W3194808133 cites W2492586371 @default.
• W3194808133 cites W2521215546 @default.
• W3194808133 cites W2578756457 @default.
• W3194808133 cites W2599500356 @default.
• W3194808133 cites W2790230321 @default.
• W3194808133 cites W2800780290 @default.
• W3194808133 cites W2814710923 @default.
• W3194808133 cites W2903546516 @default.
• W3194808133 cites W2904871403 @default.
• W3194808133 cites W2907750714 @default.
• W3194808133 cites W2912361013 @default.
• W3194808133 cites W2915483120 @default.
• W3194808133 cites W2949736877 @default.
• W3194808133 cites W2963446712 @default.
• W3194808133 cites W2963881378 @default.
• W3194808133 cites W2990986966 @default.
• W3194808133 cites W3004766715 @default.
• W3194808133 cites W3010846872 @default.
• W3194808133 cites W3012555526 @default.
• W3194808133 cites W3017240201 @default.
• W3194808133 cites W3030768590 @default.
• W3194808133 cites W3035335060 @default.
• W3194808133 cites W3037891846 @default.
• W3194808133 cites W3048285196 @default.
• W3194808133 cites W3080558256 @default.
• W3194808133 cites W3081183014 @default.
• W3194808133 cites W3083587759 @default.
• W3194808133 cites W3091852895 @default.
• W3194808133 cites W3097387309 @default.
• W3194808133 cites W3111915298 @default.
• W3194808133 cites W3119884910 @default.
• W3194808133 cites W3135903521 @default.
• W3194808133 cites W3163894833 @default.
• W3194808133 cites W3182928821 @default.
• W3194808133 doi "https://doi.org/10.1109/jstars.2021.3101203" @default.
• W3194808133 hasPublicationYear "2021" @default.
• W3194808133 type Work @default.
• W3194808133 sameAs 3194808133 @default.
• W3194808133 citedByCount "32" @default.
• W3194808133 countsByYear W31948081332021 @default.
• W3194808133 countsByYear W31948081332022 @default.
• W3194808133 countsByYear W31948081332023 @default.
• W3194808133 crossrefType "journal-article" @default.
• W3194808133 hasAuthorship W3194808133A5054292278 @default.
• W3194808133 hasAuthorship W3194808133A5063163226 @default.
• W3194808133 hasAuthorship W3194808133A5063406632 @default.
• W3194808133 hasAuthorship W3194808133A5084606868 @default.
• W3194808133 hasBestOaLocation W31948081331 @default.
• W3194808133 hasConcept C119857082 @default.
• W3194808133 hasConcept C124101348 @default.
• W3194808133 hasConcept C127413603 @default.
• W3194808133 hasConcept C138885662 @default.
• W3194808133 hasConcept C153180895 @default.
• W3194808133 hasConcept C154945302 @default.
• W3194808133 hasConcept C186295008 @default.
• W3194808133 hasConcept C187320778 @default.
• W3194808133 hasConcept C2776401178 @default.
• W3194808133 hasConcept C41008148 @default.
• W3194808133 hasConcept C41895202 @default.
• W3194808133 hasConcept C52622490 @default.
• W3194808133 hasConcept C81363708 @default.
• W3194808133 hasConcept C89600930 @default.
• W3194808133 hasConceptScore W3194808133C119857082 @default.
• W3194808133 hasConceptScore W3194808133C124101348 @default.
• W3194808133 hasConceptScore W3194808133C127413603 @default.
• W3194808133 hasConceptScore W3194808133C138885662 @default.
• W3194808133 hasConceptScore W3194808133C153180895 @default.
• W3194808133 hasConceptScore W3194808133C154945302 @default.
• W3194808133 hasConceptScore W3194808133C186295008 @default.
• W3194808133 hasConceptScore W3194808133C187320778 @default.

• next