BUILDING OUTLINE EXTRACTION FROM AERIAL IMAGERY AND DIGITAL SURFACE MODEL WITH A FRAME FIELD LEARNING FRAMEWORK

Autor: X. Sun, W. Zhao, R. V. Maretto, C. Persello

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2021, Pp 487-493 (2021)

Deep learning-based semantic segmentation models for building delineation face the challenge of producing precise and regular building outlines. Recently, a building delineation method based on frame field learning was proposed by Girard et al. (2020

Externí odkaz: https://doaj.org/article/207da006245b42a9889a150baaba80ca

LAND USE CLASSIFICATION USING DEEP MULTITASK NETWORKS

Autor: J. R. Bergado, C. Persello, A. Stein

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2020, Pp 17-21 (2020)

Updated information on urban land use allows city planners and decision makers to conduct large scale monitoring of urban areas for sustainable urban growth. Remote sensing data and classification methods offer an efficient and reliable way to update

Externí odkaz: https://doaj.org/article/54ad0559f30e4064ad2afea78ff17a51

UAV IMAGES AND DEEP-LEARNING ALGORITHMS FOR DETECTING FLAVESCENCE DOREE DISEASE IN GRAPEVINE ORCHARDS

Autor: M. A. Musci, C. Persello, A. M. Lingua

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2020, Pp 1483-1489 (2020)

One of the major challenges in precision viticulture in Europe is the detection and mapping of flavescence dorée (FD) grapevine disease to monitor and contain its spread. The lack of effective cures and the need for sustainable preventive measures a

Externí odkaz: https://doaj.org/article/d99df80de16b4756bdf2d4a8425b7b4a

SNOW AND CLOUD DISCRIMINATION USING CONVOLUTIONAL NEURAL NETWORKS

Autor: D. Varshney, P. K. Gupta, C. Persello, B. R. Nikam

Publikováno v: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol IV-5, Pp 59-63 (2018)

Snow is an important feature on our planet, and measuring its extent has advantages in climate studies. Snow mapping through satellite remote sensing is often affected by cloud cover. This issue can be resolved by using short wave infrared (SWIR) sen

Externí odkaz: https://doaj.org/article/82697960b4234bb2afc06463967dea46

CLASSIFICATION OF INFORMAL SETTLEMENTS THROUGH THE INTEGRATION OF 2D AND 3D FEATURES EXTRACTED FROM UAV DATA

Autor: C. M. Gevaert, C. Persello, R. Sliuzas, G. Vosselman

Publikováno v: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol III-3, Pp 317-324 (2016)

Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification an

Externí odkaz: https://doaj.org/article/59ed798a3efb4aa8af0c4e2b341ab579