Federated Class-Incremental Learning (FCIL) aims to design privacy-preserving collaborative training methods to continuously learn new classes from distributed datasets. In these scenarios, federated clients face the ...
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Efficient task scheduling and resource allocation are essential for optimizing performance in cloud computing environments. The presence of priority constraints necessitates advanced solutions capable of addressing th...
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Background In recent years,the demand for interactive photorealistic three-dimensional(3D)environments has increased in various fields,including architecture,engineering,and ***,achieving a balance between the quality...
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Background In recent years,the demand for interactive photorealistic three-dimensional(3D)environments has increased in various fields,including architecture,engineering,and ***,achieving a balance between the quality and efficiency of high-performance 3D applications and virtual reality(VR)remains *** This study addresses this issue by revisiting and extending view interpolation for image-based rendering(IBR),which enables the exploration of spacious open environments in 3D and ***,we introduce multimorphing,a novel rendering method based on the spatial data structure of 2D image patches,called the image *** this approach,novel views can be rendered with up to six degrees of freedom using only a sparse set of *** rendering process does not require 3D reconstruction of the geometry or per-pixel depth information,and all relevant data for the output are extracted from the local morphing cells of the image *** detection of parallax image regions during preprocessing reduces rendering artifacts by extrapolating image patches from adjacent cells in *** addition,a GPU-based solution was presented to resolve exposure inconsistencies within a dataset,enabling seamless transitions of brightness when moving between areas with varying light *** Experiments on multiple real-world and synthetic scenes demonstrate that the presented method achieves high"VR-compatible"frame rates,even on mid-range and legacy hardware,*** achieving adequate visual quality even for sparse datasets,it outperforms other IBR and current neural rendering *** Using the correspondence-based decomposition of input images into morphing cells of 2D image patches,multidimensional image morphing provides high-performance novel view generation,supporting open 3D and VR ***,the handling of morphing artifacts in the parallax image regions remains a topic for future resea
Distributed Denial of Service (DDoS) attacks are distributed at a faster rate, and they are considered to be fatal threats over the Internet. Moreover, several deep learning approaches are insufficient to attain the m...
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The factors like production accuracy and completion time are the determinants of the optimal scheduling of the complex products work-flow,so the main research direction of modern work-flow technology is how to assure ...
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The factors like production accuracy and completion time are the determinants of the optimal scheduling of the complex products work-flow,so the main research direction of modern work-flow technology is how to assure the dynamic balance between the *** on the work-flow technology,restraining the completion time,and analyzing the deficiency of traditional minimum critical path algorithm,a virtual iterative reduction algorithm(VIRA)was proposed,which can improve production accuracy effectively with time *** VIRA with simplification as the core abstracts a virtual task that can predigest the process by combining the complex structures which are cyclic or parallel,finally,by using the virtual task and the other task in the process which is the iterative reduction strategy,determines a path which can make the production accuracy and completion time more balanced than the minimum critical path *** deadline,the number of tasks,and the number of cyclic structures were used as the factors affecting the performance of the algorithm,changing the influence factors can improve the performance of the algorithm effectively through the analysis of detailed ***,comparison experiments proved the feasibility of the VIRA.
To generate dance that temporally and aesthetically matches the music is a challenging problem in three ***,the generated motion should be beats-aligned to the local musical ***,the global aesthetic style should be ma...
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To generate dance that temporally and aesthetically matches the music is a challenging problem in three ***,the generated motion should be beats-aligned to the local musical ***,the global aesthetic style should be matched between motion and *** third,the generated motion should be diverse and *** address these challenges,we propose ReChoreoNet,which re-choreographs high-quality dance motion for a given piece of music.A data-driven learning strategy is proposed to efficiently correlate the temporal connections between music and motion in a progressively learned cross-modality embedding *** beats-aligned content motion will be subsequently used as autoregressive context and control signal to control a normalizing-flow model,which transfers the style of a prototype motion to the final generated *** addition,we present an aesthetically labelled music-dance repertoire(MDR)for both efficient learning of the cross-modality embedding,and understanding of the aesthetic connections between music and *** demonstrate that our repertoire-based framework is robustly extensible in both content and *** quantitative and qualitative experiments have been carried out to validate the efficiency of our proposed model.
Balancing time,cost,and quality is crucial in intelligent ***,finding the optimal value of production parameters is a challengingnon-deterministic polynomial(NP)-hard *** the actual production process,the production p...
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Balancing time,cost,and quality is crucial in intelligent ***,finding the optimal value of production parameters is a challengingnon-deterministic polynomial(NP)-hard *** the actual production process,the production process has the characteristics of multi-stage ***,aiming at the difficult problem of multi-stage nonlinear production process optimization,this paper proposes a workflow optimization algorithm based on virtualization and nonlinear production quality under time constraints(T-OVQT).The algorithm proposed in this paper first abstracts the actual production process into a virtual workflow model,which is divided into three layers:The bottom production process collection layer,the middle layer of service node partial order composition layer,and the high level of virtual node collection ***,the virtual technology is used to reconstruct the node set and divide the task *** optimal solution is obtained through inverse iterative normalization and forward scheduling,and the global optimal solution is obtained by algorithm *** results demonstrate that this algorithm better meets actual production requirements than the traditional minimum critical path(MCP)algorithm.
Recently,Generative Adversarial Networks(GANs)have become the mainstream text-to-image(T2I)***,a standard normal distribution noise of inputs cannot provide sufficient information to synthesize an image that approache...
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Recently,Generative Adversarial Networks(GANs)have become the mainstream text-to-image(T2I)***,a standard normal distribution noise of inputs cannot provide sufficient information to synthesize an image that approaches the ground-truth image ***,the multistage generation strategy results in complex T2I ***,this study proposes a novel feature-grounded single-stage T2I model,which considers the“real”distribution learned from training images as one input and introduces a worst-case-optimized similarity measure into the loss function to enhance the model's generation *** results on two benchmark datasets demonstrate the competitive performance of the proposed model in terms of the Frechet inception distance and inception score compared to those of some classical and state-of-the-art models,showing the improved similarities among the generated image,text,and ground truth.
The Internet of Things (IoT) has revolutionized our lives, but it has also introduced significant security and privacy challenges. The vast amount of data collected by these devices, often containing sensitive informa...
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Thyroid disorders are increasingly prevalent, making early detection crucial for reducing mortality and complications. Accurate prediction of disease progression and understanding the interplay of clinical features ar...
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