Matches in SemOpenAlex for { <https://semopenalex.org/work/W3035304475> ?p ?o ?g. }
- W3035304475 endingPage "1699" @default.
- W3035304475 startingPage "1686" @default.
- W3035304475 abstract "Classification of airborne laser scanning (ALS) point clouds is needed in digital cities and 3-D modeling. To efficiently recognize objects in ALS point clouds, we propose a novel hierarchical aggregated deep feature representation method, which can adequately employ spatial association of multilevel structures and deep feature discrimination. In our method, a 3-D deep learning model is constructed to represent the discriminative feature of each point cluster in a hierarchical structure by decreasing the within-class distance and increasing the between-class distance. Our method aggregates the discriminative deep features in different levels into a hierarchical aggregated deep feature that considers the spatial hierarchy and feature distinctiveness. Lastly, we build a multichannel 1-D convolutional neural network to classify the unknown points. Our tests demonstrate that the proposed hierarchical aggregated deep feature method can enhance point cloud classification results. Comparing with seven state-of-the-art methods, those results also verified the superior performance of our method." @default.
- W3035304475 created "2020-06-19" @default.
- W3035304475 creator A5011647620 @default.
- W3035304475 creator A5019944342 @default.
- W3035304475 creator A5027313468 @default.
- W3035304475 creator A5039088967 @default.
- W3035304475 creator A5067332736 @default.
- W3035304475 creator A5069802156 @default.
- W3035304475 creator A5089171585 @default.
- W3035304475 creator A5090590010 @default.
- W3035304475 date "2021-02-01" @default.
- W3035304475 modified "2023-10-14" @default.
- W3035304475 title "Hierarchical Aggregated Deep Features for ALS Point Cloud Classification" @default.
- W3035304475 cites W1590156592 @default.
- W3035304475 cites W1644641054 @default.
- W3035304475 cites W1973644502 @default.
- W3035304475 cites W1986522259 @default.
- W3035304475 cites W1987648924 @default.
- W3035304475 cites W1990077509 @default.
- W3035304475 cites W2001014393 @default.
- W3035304475 cites W2001563151 @default.
- W3035304475 cites W2006626130 @default.
- W3035304475 cites W2008893462 @default.
- W3035304475 cites W2010221273 @default.
- W3035304475 cites W2022394120 @default.
- W3035304475 cites W2048270193 @default.
- W3035304475 cites W2052794186 @default.
- W3035304475 cites W2102734279 @default.
- W3035304475 cites W2121947440 @default.
- W3035304475 cites W2133916729 @default.
- W3035304475 cites W2143516773 @default.
- W3035304475 cites W2157364932 @default.
- W3035304475 cites W2211722331 @default.
- W3035304475 cites W2292658742 @default.
- W3035304475 cites W2330711204 @default.
- W3035304475 cites W2499171049 @default.
- W3035304475 cites W2504672320 @default.
- W3035304475 cites W2513955405 @default.
- W3035304475 cites W2537499819 @default.
- W3035304475 cites W2555618208 @default.
- W3035304475 cites W2560609797 @default.
- W3035304475 cites W2562874528 @default.
- W3035304475 cites W2566265240 @default.
- W3035304475 cites W2594610669 @default.
- W3035304475 cites W2610213140 @default.
- W3035304475 cites W2766889907 @default.
- W3035304475 cites W2769699424 @default.
- W3035304475 cites W2776330782 @default.
- W3035304475 cites W2803937221 @default.
- W3035304475 cites W2804937815 @default.
- W3035304475 cites W2899349684 @default.
- W3035304475 cites W2899809394 @default.
- W3035304475 cites W2919115771 @default.
- W3035304475 cites W2949708697 @default.
- W3035304475 cites W2962731536 @default.
- W3035304475 cites W3099206234 @default.
- W3035304475 cites W4239707196 @default.
- W3035304475 doi "https://doi.org/10.1109/tgrs.2020.2997960" @default.
- W3035304475 hasPublicationYear "2021" @default.
- W3035304475 type Work @default.
- W3035304475 sameAs 3035304475 @default.
- W3035304475 citedByCount "8" @default.
- W3035304475 countsByYear W30353044752021 @default.
- W3035304475 countsByYear W30353044752022 @default.
- W3035304475 countsByYear W30353044752023 @default.
- W3035304475 crossrefType "journal-article" @default.
- W3035304475 hasAuthorship W3035304475A5011647620 @default.
- W3035304475 hasAuthorship W3035304475A5019944342 @default.
- W3035304475 hasAuthorship W3035304475A5027313468 @default.
- W3035304475 hasAuthorship W3035304475A5039088967 @default.
- W3035304475 hasAuthorship W3035304475A5067332736 @default.
- W3035304475 hasAuthorship W3035304475A5069802156 @default.
- W3035304475 hasAuthorship W3035304475A5089171585 @default.
- W3035304475 hasAuthorship W3035304475A5090590010 @default.
- W3035304475 hasConcept C108583219 @default.
- W3035304475 hasConcept C131979681 @default.
- W3035304475 hasConcept C138885662 @default.
- W3035304475 hasConcept C153180895 @default.
- W3035304475 hasConcept C154945302 @default.
- W3035304475 hasConcept C2776401178 @default.
- W3035304475 hasConcept C41008148 @default.
- W3035304475 hasConcept C41895202 @default.
- W3035304475 hasConcept C52622490 @default.
- W3035304475 hasConcept C81363708 @default.
- W3035304475 hasConcept C97931131 @default.
- W3035304475 hasConceptScore W3035304475C108583219 @default.
- W3035304475 hasConceptScore W3035304475C131979681 @default.
- W3035304475 hasConceptScore W3035304475C138885662 @default.
- W3035304475 hasConceptScore W3035304475C153180895 @default.
- W3035304475 hasConceptScore W3035304475C154945302 @default.
- W3035304475 hasConceptScore W3035304475C2776401178 @default.
- W3035304475 hasConceptScore W3035304475C41008148 @default.
- W3035304475 hasConceptScore W3035304475C41895202 @default.
- W3035304475 hasConceptScore W3035304475C52622490 @default.
- W3035304475 hasConceptScore W3035304475C81363708 @default.
- W3035304475 hasConceptScore W3035304475C97931131 @default.
- W3035304475 hasFunder F4320321001 @default.
- W3035304475 hasFunder F4320321133 @default.