Technology in the field of health care has been constantly enhanced incorporating machine learning and various other technologies for clinical decision support systems or computer-aided healthcare systems which assist...
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Device connectivity has been redefined by the rapid development of the Internet of Things (IoT) technology, enabling diverse applications in areas such as smart cities, smart homes, and healthcare. These applications ...
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Healthcare systems all over the world are strained as the COVID-19 pandemic's spread becomes more widespread. The only realistic strategy to avoid asymptomatic transmission is to monitor social distance, as there ...
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Satellite remote sensing,characterized by extensive coverage,fre-quent revisits,and continuous monitoring,provides essential data support for addressing global *** the past six decades,thousands of Earth observation s...
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Satellite remote sensing,characterized by extensive coverage,fre-quent revisits,and continuous monitoring,provides essential data support for addressing global *** the past six decades,thousands of Earth observation satellites and sensors have been deployed *** valuable Earth observation assets are contributed independently by various nations and organizations employing diverse *** poses a significant challenge in effectively discovering global Earth observation resources and realizing their full *** this paper,we describe the develop-ment of GEOSatDB,the most complete semantic database of civil Earth observation satellites developed based on a unified ontology model.A similarity matching method is used to integrate satellite information and a prompt strategy is used to extract unstructured sensor *** resulting semantic database contains 127,949 semantic statements for 2,340 remote sensing satellites and 1,021 observation *** global Earth observation capabil-ities of 195 countries worldwide have been analyzed in detail,and a concrete use case along with an associated query demonstration is *** database provides significant value in effectively facilitating the semantic understanding and sharing of Earth observa-tion resources.
Visible‐infrared person re‐identification(VI‐ReID)is a supplementary task of single‐modality re‐identification,which makes up for the defect of conventional re‐identification under insufficient *** is more chall...
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Visible‐infrared person re‐identification(VI‐ReID)is a supplementary task of single‐modality re‐identification,which makes up for the defect of conventional re‐identification under insufficient *** is more challenging than single‐modality ReID because,in addition to difficulties in pedestrian posture,camera shoot-ing angle and background change,there are also difficulties in the cross‐modality *** works only involve coarse‐grained global features in the re‐ranking calculation,which cannot effectively use fine‐grained ***,fine‐grained features are particularly important due to the lack of information in cross‐modality re‐*** this end,the Q‐center Multi‐granularity K‐reciprocal Re‐ranking Algorithm(termed QCMR)is proposed,including a Q‐nearest neighbour centre encoder(termed QNC)and a Multi‐granularity K‐reciprocal Encoder(termed MGK)for a more comprehensive feature *** converts the probe‐corresponding modality features into gallery corresponding modality features through modality transfer to narrow the modality *** takes a coarse‐grained mutual nearest neighbour as the dominant and combines a fine‐grained nearest neighbour as a supplement for similarity *** experiments on two widely used VI‐ReID benchmarks,SYSU‐MM01 and RegDB have shown that our method achieves state‐of‐the‐art ***,the mAP of SYSU‐MM01 is increased by 5.9%in all‐search mode.
This study applies single-valued neutrosophic sets, which extend the frameworks of fuzzy and intuitionistic fuzzy sets, to graph theory. We introduce a new category of graphs called Single-Valued Heptapartitioned Neut...
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Notable tech companies such as Facebook, Microsoft, Apple, Google, and a number of game companies have launched bold plans to bring the metaverse to life. It is inevitable that in the years to come, virtual worlds wil...
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In the Fog-based Environmental Monitoring system (FEMS), the frequency at which Internet of Thing (IoT) devices upload monitoring data and the frequency at which users obtain monitoring data can highly affect energy c...
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The usage of machine learning and deep learning algorithms have necessitated Artificial Intelligence'. AI is aimed at automating things by limiting human interference. It is widely used in IT, healthcare, finance,...
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Due to the characteristics of high resolution and rich texture information,visible light images are widely used for maritime ship ***,these images are suscep-tible to sea fog and ships of different sizes,which can res...
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Due to the characteristics of high resolution and rich texture information,visible light images are widely used for maritime ship ***,these images are suscep-tible to sea fog and ships of different sizes,which can result in missed detections and false alarms,ultimately resulting in lower detection *** address these issues,a novel multi-granularity feature enhancement network,MFENet,which includes a three-way dehazing module(3WDM)and a multi-granularity feature enhancement module(MFEM)is *** 3WDM eliminates sea fog interference by using an image clarity automatic classification algorithm based on three-way decisions and FFA-Net to obtain clear image ***,the MFEM improves the accuracy of detecting ships of different sizes by utilising an improved super-resolution reconstruction con-volutional neural network to enhance the resolution and semantic representation capa-bility of the feature maps from *** results demonstrate that MFENet surpasses the other 15 competing models in terms of the mean Average Pre-cision metric on two benchmark datasets,achieving 96.28%on the McShips dataset and 97.71%on the SeaShips dataset.
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