Results 31 to 40 of about 8,937 (214)
INVESTIGATING THE POTENTIAL OF DEEP NEURAL NETWORKS FOR LARGE-SCALE CLASSIFICATION OF VERY HIGH RESOLUTION SATELLITE IMAGES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 Semantic classification is a core remote sensing task as it provides the fundamental input for land-cover map generation. The very recent literature has shown the superior performance of deep convolutional neural networks (DCNN) for many classification ...
T. Postadjian +3 more
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DOTA: A Large-scale Dataset for Object Detection in Aerial Images [PDF]
, 2018 Object detection is an important and challenging problem in computer vision. Although the past decade has witnessed major advances in object detection in natural scenes, such successes have been slow to aerial imagery, not only because of the huge ...
Bai, Xiang +8 more
core +2 more sources
Remote Sensing, 2018 This paper proposes an approach for the detection of changes in multitemporal Very High Resolution (VHR) optical images acquired by different multispectral sensors.
Yady Tatiana Solano-Correa +2 more
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International Journal of Applied Earth Observations and Geoinformation, 2022 Abandoned houses (AH) present an utmost challenge confronting the urban environment in contemporary U.S. shrinking cities. Data accessibility is a major hurdle that prevents the acquisition of large-scale AH information at the individual property level ...
Shengyuan Zou, Le Wang
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Mapping Contents Analysis of WorldView-2 VHR Satellite Imagery Using Cadastral Information [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesVery High-resolution (VHR) optical satellites with a ground sampling distance (GSD) of 1m and less for nadir view began with IKONOS in 1999. There are now several VHR optical satellites.
M. Alkan +4 more
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A Framework for SAR-Optical Stereogrammetry over Urban Areas [PDF]
, 2018 Currently, numerous remote sensing satellites provide a huge volume of diverse earth observation data. As these data show different features regarding resolution, accuracy, coverage, and spectral imaging ability, fusion techniques are required to ...
Bagheri, Hossein +3 more
core +2 more sources
BUILDING SEGMENTATION FROM AIRBORNE VHR IMAGES USING MASK R-CNN [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Abstract. Up-to-date 3D building models are important for many applications. Airborne very high resolution (VHR) images often acquired annually give an opportunity to create an up-to-date 3D model. Building segmentation is often the first and utmost step. Convolutional neural networks (CNNs) draw lots of attention in interpreting VHR images as they can
K. Zhou +3 more
openaire +5 more sources
Remote Sensing, 2020 Change detection (CD), one of the primary applications of multi-temporal satellite images, is the process of identifying changes in the Earth’s surface occurring over a period of time using images of the same geographic area on different dates.
Youkyung Han +3 more
doaj +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Multisensor data analysis allows exploiting heterogeneous data regularly acquired by the many available remote sensing (RS) systems. Machine- and deep-learning methods use the information of heterogeneous sources to improve the results obtained by using ...
Luca Bergamasco +2 more
doaj +1 more source
The role of earth observation in an integrated deprived area mapping “system” for low-to-middle income countries [PDF]
, 2020 Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure.
Boo, Gianluca +11 more
core +4 more sources