2019
DOI: 10.1155/2019/6513418
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Abstract: Currently, big data is a new and hot object of research. In particular, the development of the Internet of things (IoT) results in a sharp increase in data. Enormous amounts of networking sensors are constantly collecting and transmitting data for storage and processing in the cloud including remote sensing data, environmental data, geographical data, etc. Road information extraction from remote sensing data is mainly researched in this paper. Roads are typical man-made objects. Extracting roads from remote se… Show more

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Cited by 13 publications
(3 citation statements)
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“…The binary image is a result of classification where road pixels are white and non-roads are black. The assessment of the results is performed by using the four metrics defined in [13]. The data of ground truth obtained via manual digitization.…”
Section: Classification Accuracy Assessmentmentioning
confidence: 99%
“…The binary image is a result of classification where road pixels are white and non-roads are black. The assessment of the results is performed by using the four metrics defined in [13]. The data of ground truth obtained via manual digitization.…”
Section: Classification Accuracy Assessmentmentioning
confidence: 99%
“…According to whether prior knowledge is available, the existing methods can be divided into image-based methods and prior knowledge-based methods. Image-based methods are often used to detect intersections based on road segments [11]- [13] or image features of road intersections [14]- [16]. Zhang et al [17] utilized spherical tensors in tensor voting to extract intersection from road segments.…”
Section: Introductionmentioning
confidence: 99%
“…Semiautomatic methods need user interactions when extracting roads, which may cost more time and effort [17]- [24]. Conversely, automatic methods do not require use interactions in road extraction, which is undoubtedly faster and more efficient [25]- [33].…”
Section: Introductionmentioning
confidence: 99%