High-resolution remote sensing images
WebScene classification of high spatial resolution (HSR) images can provide data support for many practical applications, such as land planning and utilization, and it has been a crucial research topic in the remote sensing (RS) community. Recently, deep learning methods driven by massive data show the impressive ability of feature learning in the field of HSR … WebFeb 1, 2024 · In recent years, large amount of high spatial-resolution remote sensing (HRRS) images are available for land-cover mapping. However, due to the complex information …
High-resolution remote sensing images
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WebJun 3, 2024 · Abstract: Image super-resolution (SR) methods can generate remote sensing images with high spatial resolution without increasing the cost of acquisition equipment, thereby providing a feasible way to improve the quality of remote sensing images. Clearly, image SR is a severe ill-posed problem. With the development of deep learning, the … WebHigh-resolution SAR images provide more detailed spatial and textural features of the Earth’s surface , opening up possibilities for high-level vision tasks in the remote sensing domain, such as building footprint extraction for urban planning and cargo ship detection for harbor monitoring. To address the limitations in remote sensing image ...
WebAug 5, 2024 · Building detection from very high resolution (VHR) optical remote sensing images, which is an essential but challenging task in remote sensing, has attracted … WebAug 6, 2024 · The effectiveness and reliability of our proposed method are verified on two high-resolution remote sensing data sets. Extensive experimental results demonstrate the superiority of the proposed method against other state-of-the-art approaches. Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 59 , Issue: 7 , July 2024 )
WebFor this purpose, a twins context aggregation network (TCANet) is proposed to perform change detection on remote sensing images. In order to reduce the loss of spatial accuracy of remote sensing images and maintain high-resolution representation, we introduce HRNet as our backbone network to initially extract the features of interest. WebMay 15, 2024 · Semantic labeling for high resolution aerial images is a fundamental and necessary task in remote sensing image analysis. It is widely used in land-use surveys, change detection, and environmental protection. Recent researches reveal the superiority of Convolutional Neural Networks (CNNs) in this task. However, multi-scale object …
WebDec 22, 2024 · In this paper, a deeply supervised attentive high-resolution network (DSAHRNet) is proposed for remote sensing image change detection. First, we design a spatial-channel attention module to decode change information from bitemporal features. The attention module is able to model spatial-wise and channel-wise contexts.
WebFeb 1, 2024 · In recent decades, road extraction from very high-resolution (VHR) remote sensing images has become popular and has attracted extensive research efforts. … siena wind orchestraWebSemi-supervised methods have made remarkable achievements via utilizing unlabeled samples for optical high-resolution remote sensing scene classification. However, the labeled data cannot be effectively combined with unlabeled data in the existing semi-supervised methods during model training. To address this issue, we present a semi … the powassan virusWebDec 1, 2024 · Abstract: Remote sensing images are primary data sources for land use classification. High spatial resolution images enable more accurate analysis and identification of land cover types. However, a higher spatial resolution also brings new challenges to the existing classification methods. the powassan virus testingWebApr 12, 2024 · Extensive floating macroalgae have drifted from the East China Sea to Japan’s offshore area, and field observation cannot sufficiently grasp their extensive spatial and temporal changes. High-spatial-resolution satellite data, which contain multiple spectral bands, have advanced remote sensing analysis. Several indexes for recognizing … sienci feeds and speedsWebDec 22, 2024 · The high-resolution 0.4m/px image from Kompsat-3A lets you clearly see buildings, roads, and even cars, but in most cases you have to pay for that level of detail. … the powbarWebFeb 1, 2024 · To our knowledge, GID is the first and largest well-annotated land-cover classification dataset with high-resolution remote sensing images up to 4 m. It can provide the research community a high-quality dataset to advance land-cover classification with HRRS images, like Gaofen-2 imagery. siena women\u0027s basketball scheduleWebAug 1, 2024 · With the development of high resolution optical sensors (e.g., WorldView-3, GeoEys-1, QuickBird, and Gaofen-2), the increasing availability of high resolution remote … siena women\u0027s soccer