A sustainably governed water-ecosystem at village-level is crucial for the community's well-being. It requires understanding natures’ limits to store and yield water and balance it with the stakeholders’ needs, ...
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Semantic segmentation provides important technical support for Land cover/land use(LCLU)*** calculating the cosine similarity between feature vectors,transformer-based models can effectively capture the global informa...
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Semantic segmentation provides important technical support for Land cover/land use(LCLU)*** calculating the cosine similarity between feature vectors,transformer-based models can effectively capture the global information of high-resolution remote sensing ***,the diversity of detailed and edge features within the same class of ground objects in high-resolution remote sensing images leads to a dispersed embedding *** dispersed feature distribution enlarges feature vector angles and reduces cosine similarity,weakening the attention mechanism’s ability to identify the same class of ground *** address this challenge,remote sensing image information granulation transformer for semantic segmentation is *** model employs adaptive granulation to extract common semantic features among objects of the same class,constructing an information granule to replace the detailed feature representation of these ***,the Laplacian operator of the information granule is applied to extract the edge features of the object as represented by the information *** the experiments,the proposed model was validated on the Beijing Land-Use(BLU),Gaofen Image Dataset(GID),and Potsdam Dataset(PD).In particular,the model achieves 88.81%for mOA,82.64%for mF1,and 71.50%for mIoU metrics on the GID *** results show that the model effectively handles high-resolution remote sensing *** code is available at https://***/sjmp525/RSIGT(accessed on 16 April 2025).
The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing s...
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The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing superpoint segmentation methods focus only on local geometric structures,resulting in inconsistent spectral features of points within a *** feature inconsistencies degrade the performance of subsequent ***,this study proposes a novel Superpoint Segmentation method that jointly utilizes spatial Geometric and Spectral Information for multispectral point cloud superpoint segmentation(GSI-SS).Specifically,a similarity metric that combines spatial geometry and spectral information is proposed to facilitate the consistency of geometric structures and object attributes within segmented *** the formation of the primary superpoints,an intersuperpoint pointexchange mechanism that maximizes feature consistency within the final superpoints is *** are conducted on two real multispectral point cloud datasets,and the proposed method achieved higher recall,precision,F score,and lower global consistency and feature classification *** experimental results demonstrate the superiority of the proposed GSI-SS over several state-of-the-art methods.
Neurodegenerative disorders such as dementia and Alzheimer’s disease (AD) have adversely devastated the health and well-being of the older community. Given that early detection might help prevent or delay cognitive d...
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The integration of machine learning (ML) into mobile applications presents unique challenges, particularly in resource-constrained environments such as iOS devices. Skin lesion classification is a critical task in der...
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Due to increased network traffic and security concerns, intrusion detection system (IDS) research has received a lot of attention in computer science. Advanced intrusion detection systems have arbitrary incursion cate...
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Short-term load forecasting (STLF) is a significant task to the planning, operation and control of future power systems. The increasing number of devices connected to the system has led to more complex characteristics...
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Finding materials with specific properties is a hot topic in materials *** materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high *** the developmen...
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Finding materials with specific properties is a hot topic in materials *** materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high *** the development of physics,statistics,computer science,and other fields,machine learning offers opportunities for systematically discovering new *** through machine learning-based inverse design,machine learning algorithms analyze the mapping relationships between materials and their properties to find materials with desired *** paper first outlines the basic concepts of materials inverse design and the challenges faced by machine learning-based approaches to materials inverse ***,three main inverse design methods—exploration-based,model-based,and optimization-based—are analyzed in the context of different application ***,the applications of inverse design methods in alloys,optical materials,and acoustic materials are elaborated on,and the prospects for materials inverse design are *** authors hope to accelerate the discovery of new materials and provide new possibilities for advancing materials science and innovative design methods.
Due to the complexity and urgency of information exchange in modern companies, optimizing communication protocols in the workplace is essential. Using methods from machine learning, this research takes a fresh tack to...
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Efficient node deployment in Wireless Sensor Networks (WSNs) is critical for maximizing network coverage, enhancing energy efficiency, and prolonging network lifetime. However, achieving optimal node placement is chal...
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