Results 51 to 60 of about 558,332 (197)
Remote Sensing, 2021 Accurate building footprint polygons provide essential data for a wide range of urban applications. While deep learning models have been proposed to extract pixel-based building areas from remote sensing imagery, the direct vectorization of pixel-based ...
Ziming Li +3 more
semanticscholar +1 more source
Aerial Imagery Pile burn detection using Deep Learning: the FLAME dataset [PDF]
Comput. Networks, 2020 Wildfires are one of the costliest and deadliest natural disasters in the US, causing damage to millions of hectares of forest resources and threatening the lives of people and animals.
Alireza Shamsoshoara +5 more
semanticscholar +1 more source
Visual place recognition for aerial imagery: A survey [PDF]
Robotics Auton. Syst.Aerial imagery and its direct application to visual localization is an essential problem for many Robotics and Computer Vision tasks. While Global Navigation Satellite Systems (GNSS) are the standard default solution for solving the aerial localization ...
Ivan Moskalenko +2 more
semanticscholar +1 more source
LandCover.ai: Dataset for Automatic Mapping of Buildings, Woodlands, Water and Roads from Aerial Imagery [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020 Monitoring of land cover and land use is crucial in natural resources management. Automatic visual mapping can carry enormous economic value for agriculture, forestry, or public administration. Satellite or aerial images combined with computer vision and
Adrian Boguszewski +4 more
semanticscholar +1 more source
VSAI: A Multi-View Dataset for Vehicle Detection in Complex Scenarios Using Aerial Images
Drones, 2022 Arbitrary-oriented vehicle detection via aerial imagery is essential in remote sensing and computer vision, with various applications in traffic management, disaster monitoring, smart cities, etc.
Jinghao Wang +5 more
doaj +1 more source
OBLIQUE AERIAL IMAGERY FOR NMA – SOME BEST PRACTICES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Abstract. Oblique airborne photogrammetry is rapidly maturing and being offered by service providers as a good alternative or replacement of the more traditional vertical imagery and for very different applications (Fig.1). EuroSDR, representing European National Mapping Agencies (NMAs) and research organizations of most EU states, is following the ...
F. Remondino +7 more
openaire +4 more sources
Classification of Soybean Pubescence from Multispectral Aerial Imagery. [PDF]
Plant Phenomics, 2021 The accurate determination of soybean pubescence is essential for plant breeding programs and cultivar registration. Currently, soybean pubescence is classified visually, which is a labor-intensive and time-consuming activity.
Bruce RW, Rajcan I, Sulik J.
europepmc +2 more sources
Remote Sensing in Ecology and Conservation, 2021 Survey and monitoring of wildlife populations are among the key elements in nature conservation. The use of unmanned aerial vehicles and light aircrafts as aerial image acquisition systems is growing, as they are cheaper alternatives to traditional ...
Alexandre Delplanque +4 more
semanticscholar +1 more source
Roof Material Classification from Aerial Imagery [PDF]
Optical Memory and Neural Networks, 2020 This paper describes an algorithm for classification of roof materials using aerial photographs. Main advantages of the algorithm are proposed methods to improve prediction accuracy. Proposed methods includes: method of converting ImageNet weights of neural networks for using multi-channel images; special set of features of second level models that are
openaire +2 more sources
Assessment of hydrogen fluoride damage to vegetation using optical remote sensing data [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 This research assesses damage to vegetation from accidental gaseous hydrogen fluoride leakage, through the analysis of spectral features of the damaged plants using digital aerial photographs and airborne hyperspectral imagery.
C. U. Hyun, J. S. Lee, I. Lee
doaj +1 more source