Matches in SemOpenAlex for { <https://semopenalex.org/work/W3120372074> ?p ?o ?g. }
Showing items 1 to 88 of
88
with 100 items per page.
- W3120372074 endingPage "451" @default.
- W3120372074 startingPage "441" @default.
- W3120372074 abstract "The detection of roads from satellite images is a heated area of research in recent years. Satellite and aerial images are the most important available data sources for map generation and updating available maps. Task of automatically detecting roads is one of the specific cases of this problem. Proposed task is a difficult foresight problem because of occulations, shadows and a huge variety of non-road objects []. This research proposes identifying roads by means of a neural network with millions of trainable weights which sees at a much bigger context than the ones used in earlier activation functions and dropout layers. Moreover, real-time image augmentation was verified to improve the accuracy of the model and avoid overfitting. According to experiments, CNN model outperforms all the other tested methodology." @default.
- W3120372074 created "2021-01-18" @default.
- W3120372074 creator A5005377808 @default.
- W3120372074 creator A5057716854 @default.
- W3120372074 creator A5087418141 @default.
- W3120372074 creator A5088620231 @default.
- W3120372074 date "2020-12-16" @default.
- W3120372074 modified "2023-09-26" @default.
- W3120372074 title "Detection of Roads in Satellite Images Using Deep Learning Technique" @default.
- W3120372074 cites W1950756354 @default.
- W3120372074 cites W1974097572 @default.
- W3120372074 cites W1981625538 @default.
- W3120372074 cites W2051874994 @default.
- W3120372074 cites W2078219094 @default.
- W3120372074 cites W2112583669 @default.
- W3120372074 cites W2143972956 @default.
- W3120372074 cites W2156044350 @default.
- W3120372074 cites W2160445453 @default.
- W3120372074 cites W2536572210 @default.
- W3120372074 cites W2559803985 @default.
- W3120372074 doi "https://doi.org/10.1007/978-981-15-8354-4_44" @default.
- W3120372074 hasPublicationYear "2020" @default.
- W3120372074 type Work @default.
- W3120372074 sameAs 3120372074 @default.
- W3120372074 citedByCount "3" @default.
- W3120372074 countsByYear W31203720742021 @default.
- W3120372074 countsByYear W31203720742022 @default.
- W3120372074 countsByYear W31203720742023 @default.
- W3120372074 crossrefType "book-chapter" @default.
- W3120372074 hasAuthorship W3120372074A5005377808 @default.
- W3120372074 hasAuthorship W3120372074A5057716854 @default.
- W3120372074 hasAuthorship W3120372074A5087418141 @default.
- W3120372074 hasAuthorship W3120372074A5088620231 @default.
- W3120372074 hasConcept C108583219 @default.
- W3120372074 hasConcept C119857082 @default.
- W3120372074 hasConcept C127413603 @default.
- W3120372074 hasConcept C146978453 @default.
- W3120372074 hasConcept C153180895 @default.
- W3120372074 hasConcept C154945302 @default.
- W3120372074 hasConcept C166957645 @default.
- W3120372074 hasConcept C19269812 @default.
- W3120372074 hasConcept C201995342 @default.
- W3120372074 hasConcept C205649164 @default.
- W3120372074 hasConcept C22019652 @default.
- W3120372074 hasConcept C2776145597 @default.
- W3120372074 hasConcept C2779343474 @default.
- W3120372074 hasConcept C2780451532 @default.
- W3120372074 hasConcept C31972630 @default.
- W3120372074 hasConcept C41008148 @default.
- W3120372074 hasConcept C50644808 @default.
- W3120372074 hasConcept C81363708 @default.
- W3120372074 hasConceptScore W3120372074C108583219 @default.
- W3120372074 hasConceptScore W3120372074C119857082 @default.
- W3120372074 hasConceptScore W3120372074C127413603 @default.
- W3120372074 hasConceptScore W3120372074C146978453 @default.
- W3120372074 hasConceptScore W3120372074C153180895 @default.
- W3120372074 hasConceptScore W3120372074C154945302 @default.
- W3120372074 hasConceptScore W3120372074C166957645 @default.
- W3120372074 hasConceptScore W3120372074C19269812 @default.
- W3120372074 hasConceptScore W3120372074C201995342 @default.
- W3120372074 hasConceptScore W3120372074C205649164 @default.
- W3120372074 hasConceptScore W3120372074C22019652 @default.
- W3120372074 hasConceptScore W3120372074C2776145597 @default.
- W3120372074 hasConceptScore W3120372074C2779343474 @default.
- W3120372074 hasConceptScore W3120372074C2780451532 @default.
- W3120372074 hasConceptScore W3120372074C31972630 @default.
- W3120372074 hasConceptScore W3120372074C41008148 @default.
- W3120372074 hasConceptScore W3120372074C50644808 @default.
- W3120372074 hasConceptScore W3120372074C81363708 @default.
- W3120372074 hasLocation W31203720741 @default.
- W3120372074 hasOpenAccess W3120372074 @default.
- W3120372074 hasPrimaryLocation W31203720741 @default.
- W3120372074 hasRelatedWork W2767651786 @default.
- W3120372074 hasRelatedWork W2981481749 @default.
- W3120372074 hasRelatedWork W2997709384 @default.
- W3120372074 hasRelatedWork W3099765033 @default.
- W3120372074 hasRelatedWork W3128220493 @default.
- W3120372074 hasRelatedWork W3186919929 @default.
- W3120372074 hasRelatedWork W4220996320 @default.
- W3120372074 hasRelatedWork W4283701629 @default.
- W3120372074 hasRelatedWork W4309224979 @default.
- W3120372074 hasRelatedWork W4313289428 @default.
- W3120372074 isParatext "false" @default.
- W3120372074 isRetracted "false" @default.
- W3120372074 magId "3120372074" @default.
- W3120372074 workType "book-chapter" @default.