FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3044239698> ?p ?o ?g. }

• W3044239698 endingPage "2379" @default.
• W3044239698 startingPage "2379" @default.
• W3044239698 abstract "Detecting individual trees and quantifying their biomass is crucial for carbon accounting procedures at the stand, landscape, and national levels. A significant challenge for many organizations is the amount of effort necessary to document carbon storage levels, especially in terms of human labor. To advance towards the goal of efficiently assessing the carbon content of forest, we evaluate methods to detect trees from high-resolution images taken from unoccupied aerial systems (UAS). In the process, we introduce the Digital Elevated Vegetation Model (DEVM), a representation that combines multispectral images, digital surface models, and digital terrain models. We show that the DEVM facilitates the development of refined synthetic data to detect individual trees using deep learning-based approaches. We carried out experiments in two tree fields located in different countries. Simultaneously, we perform comparisons among an array of classical and deep learning-based methods highlighting the precision and reliability of the DEVM." @default.
• W3044239698 created "2020-07-29" @default.
• W3044239698 creator A5024505600 @default.
• W3044239698 creator A5040592444 @default.
• W3044239698 creator A5061947528 @default.
• W3044239698 creator A5063658743 @default.
• W3044239698 creator A5081073767 @default.
• W3044239698 date "2020-07-24" @default.
• W3044239698 modified "2023-10-17" @default.
• W3044239698 title "Assessment of Tree Detection Methods in Multispectral Aerial Images" @default.
• W3044239698 cites W1949157008 @default.
• W3044239698 cites W1967395374 @default.
• W3044239698 cites W1970822048 @default.
• W3044239698 cites W1982886002 @default.
• W3044239698 cites W1990503995 @default.
• W3044239698 cites W2031489346 @default.
• W3044239698 cites W2115579991 @default.
• W3044239698 cites W2125556102 @default.
• W3044239698 cites W2144158466 @default.
• W3044239698 cites W2146532890 @default.
• W3044239698 cites W2149324144 @default.
• W3044239698 cites W2176950688 @default.
• W3044239698 cites W2425734797 @default.
• W3044239698 cites W2565950292 @default.
• W3044239698 cites W2578363764 @default.
• W3044239698 cites W2600176623 @default.
• W3044239698 cites W2610147853 @default.
• W3044239698 cites W2743744664 @default.
• W3044239698 cites W2767007666 @default.
• W3044239698 cites W2787518617 @default.
• W3044239698 cites W2791405895 @default.
• W3044239698 cites W2791456092 @default.
• W3044239698 cites W2793323341 @default.
• W3044239698 cites W2801211594 @default.
• W3044239698 cites W2803921148 @default.
• W3044239698 cites W2890137203 @default.
• W3044239698 cites W2891195071 @default.
• W3044239698 cites W2894527439 @default.
• W3044239698 cites W2901867974 @default.
• W3044239698 cites W2902926688 @default.
• W3044239698 cites W2906300491 @default.
• W3044239698 cites W2911363843 @default.
• W3044239698 cites W2911709005 @default.
• W3044239698 cites W2914321566 @default.
• W3044239698 cites W2921271497 @default.
• W3044239698 cites W2943693653 @default.
• W3044239698 cites W2952142982 @default.
• W3044239698 cites W2954633720 @default.
• W3044239698 cites W2963221299 @default.
• W3044239698 cites W2967268202 @default.
• W3044239698 cites W2988389512 @default.
• W3044239698 cites W3004568742 @default.
• W3044239698 cites W3004769717 @default.
• W3044239698 cites W3005872463 @default.
• W3044239698 cites W3012039216 @default.
• W3044239698 cites W3026814163 @default.
• W3044239698 cites W3027817129 @default.
• W3044239698 cites W4254171388 @default.
• W3044239698 cites W4288863712 @default.
• W3044239698 cites W2002863131 @default.
• W3044239698 doi "https://doi.org/10.3390/rs12152379" @default.
• W3044239698 hasPublicationYear "2020" @default.
• W3044239698 type Work @default.
• W3044239698 sameAs 3044239698 @default.
• W3044239698 citedByCount "10" @default.
• W3044239698 countsByYear W30442396982021 @default.
• W3044239698 countsByYear W30442396982022 @default.
• W3044239698 countsByYear W30442396982023 @default.
• W3044239698 crossrefType "journal-article" @default.
• W3044239698 hasAuthorship W3044239698A5024505600 @default.
• W3044239698 hasAuthorship W3044239698A5040592444 @default.
• W3044239698 hasAuthorship W3044239698A5061947528 @default.
• W3044239698 hasAuthorship W3044239698A5063658743 @default.
• W3044239698 hasAuthorship W3044239698A5081073767 @default.
• W3044239698 hasBestOaLocation W30442396981 @default.
• W3044239698 hasConcept C111919701 @default.
• W3044239698 hasConcept C113174947 @default.
• W3044239698 hasConcept C134306372 @default.
• W3044239698 hasConcept C142724271 @default.
• W3044239698 hasConcept C154945302 @default.
• W3044239698 hasConcept C161840515 @default.
• W3044239698 hasConcept C173163844 @default.
• W3044239698 hasConcept C176262533 @default.
• W3044239698 hasConcept C17744445 @default.
• W3044239698 hasConcept C199539241 @default.
• W3044239698 hasConcept C205649164 @default.
• W3044239698 hasConcept C2776133958 @default.
• W3044239698 hasConcept C2776359362 @default.
• W3044239698 hasConcept C33923547 @default.
• W3044239698 hasConcept C41008148 @default.
• W3044239698 hasConcept C58640448 @default.
• W3044239698 hasConcept C62649853 @default.
• W3044239698 hasConcept C71924100 @default.
• W3044239698 hasConcept C94625758 @default.
• W3044239698 hasConcept C98045186 @default.
• W3044239698 hasConceptScore W3044239698C111919701 @default.
• W3044239698 hasConceptScore W3044239698C113174947 @default.
• W3044239698 hasConceptScore W3044239698C134306372 @default.

• next