Image-based synthetic aperture radar (SAR) target three-dimensional (3D) reconstruction is an important application for extracting target information from high-resolution two-dimensional (2D) SAR images. However, due ...
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Urban flow monitoring and forecasting systems play important roles in smart city management. However, due to the long-lasting and enormous deployment cost of ubiquitous traffic monitoring devices (e.g., loop detectors...
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As the electromagnetic environment in battlefields becomes increasingly complex, automatic modulation recognition for noncooperation radiation source signal is becoming vital and challenging. Most previous works were ...
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Mangroves are crucial to the ecological security of the Earth and human *** management,conservation,and restoration are of great importance and necessitate the support of spatio-temporal information and multidisciplin...
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Mangroves are crucial to the ecological security of the Earth and human *** management,conservation,and restoration are of great importance and necessitate the support of spatio-temporal information and multidisciplinary knowledge such as biology and *** knowledge services such as plant atlas provide illustrated textual knowledge of ***,this kind of service is oriented to information retrieval and is incapable of effectively mining and utilizing fragmented knowledge from multi-source heterogeneous data,facing the problem of“massive data,rare knowledge”.Knowledge graphs are capable of extracting,organizing,and fusing the knowledge contained in massive data into semantic networks that can be understood and computed by *** provide a solution for the realization of intelligent knowledge *** on the urgent need for mangrove knowledge acquisition,formal representation,and intelligent services,this paper proposes a research prospect on mangrove knowledge graphs and knowledge *** first analyze the similarities and differences between various domain-specific concepts of *** this basis,we define the mangrove knowledge graph as a large-scale knowledge base that integrates multi-disciplinary knowledge and spatio-temporal information with mangrove ecosystems as the ***,we propose a research framework for mangrove knowledge services that can realize the transformation from multi-modal data to intelligent knowledge services,including multiple research levels such as ubiquitous data sensing and aggregation,knowledge organization and graph construction,and intelligent mangrove knowledge ***,the methods and workflow for constructing mangrove knowledge graphs are ***,we discuss the challenges and possible future directions of mangrove knowledge services in the smart era,including the construction of a mangrove knowledge system that integrates the domain-specific charac
High resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolu...
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End-to-end image coding methods based on wavelet-like transform have made great progress in recent years. The most advanced one is iWave++, which adopts multi-level lifting schemes based on convolutional neural networ...
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Characterizing foliar trait variation in sun and shade leaves can provide insights into inter-and intra-species resource use strategies and plant response to environmental ***,datasets with records of multiple foliar ...
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Characterizing foliar trait variation in sun and shade leaves can provide insights into inter-and intra-species resource use strategies and plant response to environmental ***,datasets with records of multiple foliar traits from the same individual and including shade leaves are sparse,which limits our ability to investigate trait-trait,trait-environment relationships and trait coordination in both sun and shade *** presented a comprehensive dataset of 15 foliar traits from sun and shade leaves sampled with leaf spectroscopy,including 424 individuals of 110 plant species from 19 sites across eastern North *** investigated trait variation,covariation,scaling relationships with leaf mass,and the effects of environment,canopy position,and taxonomy on trait ***,sun leaves had higher leaf mass per area,nonstructural carbohydrates and total phenolics,lower mass-based chlorophyll a+b,carotenoids,phosphorus,and potassium,but exhibited species-specific *** between sun and shade leaf traits,and trait-environment relationships were overall consistent across *** main dimensions of foliar trait variation in seed plants were revealed including leaf economics traits,photosynthetic pigments,defense,and structural *** and canopy position collectively explained most of the foliar trait *** study highlights the importance of including intra-individual and intra-specific trait variation to improve our understanding of ecosystem *** findings have implications for efficient field sampling,and trait mapping with remote sensing.
Stacking is the process of overlaying inferred species potential distributions for multiple species based on outputs of bioclimatic envelope models(BEMs).The approach can be used to investigate patterns and processes ...
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Stacking is the process of overlaying inferred species potential distributions for multiple species based on outputs of bioclimatic envelope models(BEMs).The approach can be used to investigate patterns and processes of species *** data limitations on individual species distributions are inevitable,but how do they affect inferences of patterns and processes of species richness?We investigate the influence of different data sources on estimated species richness gradients in *** fitted BEMs using species distributions data for 334 bird species obtained from(1)global range maps,(2)regional checklists,(3)museum records and surveys,and(4)citizen science data using presence-only(Mahalanobis distance),presence-background(MAXENT),and presence–absence(GAM and BRT)*** species predictions were stacked to generate species richness ***,we show that different data sources and BEMs can generate spatially varying gradients of species *** environmental predictors that best explained species distributions also differed between data *** using citizen-based data had the highest accuracy,whereas those using range data had the lowest *** richness patterns estimated by GAM and BRT models were robust to data *** multiple data sets exist for the same region and taxa,we advise that explicit treatments of uncertainty,such as sensitivity analyses of the input data,should be conducted during the process of modeling.
The Two-step algorithm (TSA) is widely used for trajectory deviation compensation of airborne Synthetic aperture radar (SAR), by which most of the motion errors are compensated before Range curve migration compensatio...
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The Two-step algorithm (TSA) is widely used for trajectory deviation compensation of airborne Synthetic aperture radar (SAR), by which most of the motion errors are compensated before Range curve migration compensation (RCMC) and the residual after the RCMC. We found that the RCMC in the presence of the residual motion errors results in additional range shift errors hard to be compensated for. Based on theoretical investigations, this shortage of TSA is reported and a new compensation scheme which greatly alleviates the RCMC induced errors is proposed. Besides, range resampling considering the residual motion errors is very convinent, which, however, is boresome in TSA. The new method is effective to compensate the high resolution SAR systems for large trajectory deviations, which is hard to be achieved by TSA because of the uncompensated errors. Results on the simulated data are provided to demonstrate the effectiveness of the new method.
This study introduces a novel few-shot instance segmentation framework MAR FSIS for identifying and segmenting aircraft in high-resolution remote sensing imagery under stringent few-shot conditions. Utilizing large vi...
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ISBN:
(数字)9798350360325
ISBN:
(纸本)9798350360332
This study introduces a novel few-shot instance segmentation framework MAR FSIS for identifying and segmenting aircraft in high-resolution remote sensing imagery under stringent few-shot conditions. Utilizing large vision models in conjunction with a sophisticated detector and a novel object prompter, MAR FSIS demonstrates superior performance in discerning intricate details of aircraft with minimal training examples. The effectiveness of this approach is confirmed through experimental evaluations on the proposed MAR20IS dataset, achieving remarkable precision in both detection and segmentation tasks.
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