Matches in SemOpenAlex for { <https://semopenalex.org/work/W3213598098> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W3213598098 endingPage "77" @default.
- W3213598098 startingPage "67" @default.
- W3213598098 abstract "Semantic segmentation of Lidar data using Deep Learning (DL) is a fundamental step for a deep and rigorous understanding of large-scale urban areas. Indeed, the increasing development of Lidar technology in terms of accuracy and spatial resolution offers a best opportunity for delivering a reliable semantic segmentation in large-scale urban environments. Significant progress has been reported in this direction. However, the literature lacks a deep comparison of the existing methods and algorithms in terms of strengths and weakness. The aim of the present paper is therefore to propose an objective review about these methods by highlighting their strengths and limitations. We then propose a new approach based on the combination of Lidar data and other sources in conjunction with a Deep Learning technique whose objective is to automatically extract semantic information from airborne Lidar point clouds by enhancing both accuracy and semantic precision compared to the existing methods. We finally present the first results of our approach." @default.
- W3213598098 created "2021-11-22" @default.
- W3213598098 creator A5045433356 @default.
- W3213598098 creator A5057655138 @default.
- W3213598098 creator A5072219045 @default.
- W3213598098 date "2021-11-11" @default.
- W3213598098 modified "2023-09-26" @default.
- W3213598098 title "Toward a Deep Learning Approach for Automatic Semantic Segmentation of 3D Lidar Point Clouds in Urban Areas" @default.
- W3213598098 cites W1901129140 @default.
- W3213598098 cites W2117186870 @default.
- W3213598098 cites W2194775991 @default.
- W3213598098 cites W250737475 @default.
- W3213598098 cites W2556802233 @default.
- W3213598098 cites W2594519801 @default.
- W3213598098 cites W2594610669 @default.
- W3213598098 cites W2606643123 @default.
- W3213598098 cites W2621083258 @default.
- W3213598098 cites W2775216572 @default.
- W3213598098 cites W2788158258 @default.
- W3213598098 cites W2800306924 @default.
- W3213598098 cites W2804532080 @default.
- W3213598098 cites W2809426059 @default.
- W3213598098 cites W2901506785 @default.
- W3213598098 cites W2943210864 @default.
- W3213598098 cites W2962912109 @default.
- W3213598098 cites W2963226018 @default.
- W3213598098 cites W2963281829 @default.
- W3213598098 cites W2963881378 @default.
- W3213598098 cites W2981949127 @default.
- W3213598098 cites W2982649931 @default.
- W3213598098 cites W3012494314 @default.
- W3213598098 cites W3015248322 @default.
- W3213598098 cites W3091848145 @default.
- W3213598098 cites W3105636206 @default.
- W3213598098 doi "https://doi.org/10.1007/978-3-030-80458-9_6" @default.
- W3213598098 hasPublicationYear "2021" @default.
- W3213598098 type Work @default.
- W3213598098 sameAs 3213598098 @default.
- W3213598098 citedByCount "0" @default.
- W3213598098 crossrefType "book-chapter" @default.
- W3213598098 hasAuthorship W3213598098A5045433356 @default.
- W3213598098 hasAuthorship W3213598098A5057655138 @default.
- W3213598098 hasAuthorship W3213598098A5072219045 @default.
- W3213598098 hasBestOaLocation W32135980982 @default.
- W3213598098 hasConcept C108583219 @default.
- W3213598098 hasConcept C119857082 @default.
- W3213598098 hasConcept C131979681 @default.
- W3213598098 hasConcept C154945302 @default.
- W3213598098 hasConcept C184337299 @default.
- W3213598098 hasConcept C199360897 @default.
- W3213598098 hasConcept C205649164 @default.
- W3213598098 hasConcept C2524010 @default.
- W3213598098 hasConcept C2778755073 @default.
- W3213598098 hasConcept C28719098 @default.
- W3213598098 hasConcept C33923547 @default.
- W3213598098 hasConcept C41008148 @default.
- W3213598098 hasConcept C51399673 @default.
- W3213598098 hasConcept C58640448 @default.
- W3213598098 hasConcept C62649853 @default.
- W3213598098 hasConcept C89600930 @default.
- W3213598098 hasConceptScore W3213598098C108583219 @default.
- W3213598098 hasConceptScore W3213598098C119857082 @default.
- W3213598098 hasConceptScore W3213598098C131979681 @default.
- W3213598098 hasConceptScore W3213598098C154945302 @default.
- W3213598098 hasConceptScore W3213598098C184337299 @default.
- W3213598098 hasConceptScore W3213598098C199360897 @default.
- W3213598098 hasConceptScore W3213598098C205649164 @default.
- W3213598098 hasConceptScore W3213598098C2524010 @default.
- W3213598098 hasConceptScore W3213598098C2778755073 @default.
- W3213598098 hasConceptScore W3213598098C28719098 @default.
- W3213598098 hasConceptScore W3213598098C33923547 @default.
- W3213598098 hasConceptScore W3213598098C41008148 @default.
- W3213598098 hasConceptScore W3213598098C51399673 @default.
- W3213598098 hasConceptScore W3213598098C58640448 @default.
- W3213598098 hasConceptScore W3213598098C62649853 @default.
- W3213598098 hasConceptScore W3213598098C89600930 @default.
- W3213598098 hasLocation W32135980981 @default.
- W3213598098 hasLocation W32135980982 @default.
- W3213598098 hasOpenAccess W3213598098 @default.
- W3213598098 hasPrimaryLocation W32135980981 @default.
- W3213598098 hasRelatedWork W1557295345 @default.
- W3213598098 hasRelatedWork W2335177719 @default.
- W3213598098 hasRelatedWork W2917062864 @default.
- W3213598098 hasRelatedWork W2959771705 @default.
- W3213598098 hasRelatedWork W2976989770 @default.
- W3213598098 hasRelatedWork W2994780231 @default.
- W3213598098 hasRelatedWork W3212121815 @default.
- W3213598098 hasRelatedWork W3213598098 @default.
- W3213598098 hasRelatedWork W4226195147 @default.
- W3213598098 hasRelatedWork W4310264062 @default.
- W3213598098 isParatext "false" @default.
- W3213598098 isRetracted "false" @default.
- W3213598098 magId "3213598098" @default.
- W3213598098 workType "book-chapter" @default.