In this article, we present the first rigorous theoretical analysis of the generalisation performance of a Geometric Semantic Genetic Programming (GSGP) system. More specifically, we consider a hill-climber using the ...
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This paper examines fault-tolerant quantized control for neural networks under persistent dwell-time switching, considering the presence of actuator faults and dynamic output quantization. The dynamic scaling factor (...
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Data collection using mobile sink(s) has proven to reduce energy consumption and enhance the network lifetime of wireless sensor networks. Generally speaking, a mobile sink (MS) traverses the network region, sojournin...
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Diabetes disease is prevalent worldwide, and predicting its progression is crucial. Several model have been proposed to predict such disease. Those models only determine the disease label, leaving the likelihood of de...
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Direct part-level manipulation of man-made shapes in an image is desired given its simplicity. However, it is not intuitive given the existing manually created cuboid and cylinder controllers. To tackle this problem, ...
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Higher-order patterns reveal sequential multistep state transitions,which are usually superior to origin-destination analyses that depict only first-order geospatial movement *** methods for higher-order movement mode...
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Higher-order patterns reveal sequential multistep state transitions,which are usually superior to origin-destination analyses that depict only first-order geospatial movement *** methods for higher-order movement modeling first construct a directed acyclic graph(DAG)of movements and then extract higher-order patterns from the ***,DAG-based methods rely heavily on identifying movement keypoints,which are challenging for sparse movements and fail to consider the temporal variants critical for movements in urban *** overcome these limitations,we propose HoLens,a novel approach for modeling and visualizing higher-order movement patterns in the context of an urban *** mainly makes twofold contributions:First,we designed an auto-adaptive movement aggregation algorithm that self-organizes movements hierarchically by considering spatial proximity,contextual information,and tem-poral ***,we developed an interactive visual analytics interface comprising well-established visualization techniques,including the H-Flow for visualizing the higher-order patterns on the map and the higher-order state sequence chart for representing the higher-order state *** real-world case studies demonstrate that the method can adaptively aggregate data and exhibit the process of exploring higher-order patterns using *** also demonstrate the feasibility,usability,and effectiveness of our approach through expert interviews with three domain experts.
We present a novel framework for the multidomain synthesis of artworks from semantic *** of the main limitations of this challenging task is the lack of publicly available segmentation datasets for art *** address thi...
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We present a novel framework for the multidomain synthesis of artworks from semantic *** of the main limitations of this challenging task is the lack of publicly available segmentation datasets for art *** address this problem,we propose a dataset called ArtSem that contains 40,000 images of artwork from four different domains,with their corresponding semantic label *** first extracted semantic maps from landscape photography and used a conditional generative adversarial network(GAN)-based approach for generating high-quality artwork from semantic maps without requiring paired training ***,we propose an artwork-synthesis model using domain-dependent variational encoders for high-quality multi-domain ***,the model was improved and complemented with a simple but effective normalization method based on jointly normalizing semantics and style,which we call spatially style-adaptive normalization(SSTAN).Compared to the previous methods,which only take semantic layout as the input,our model jointly learns style and semantic information representation,improving the generation quality of artistic *** results indicate that our model learned to separate the domains in the latent ***,we can perform fine-grained control of the synthesized artwork by identifying hyperplanes that separate the different ***,by combining the proposed dataset and approach,we generated user-controllable artworks of higher quality than that of existing approaches,as corroborated by quantitative metrics and a user study.
Lung cancer is a prevalent and deadly disease worldwide, necessitating accurate and timely detection methods for effective treatment. Deep learning-based approaches have emerged as promising solutions for automated me...
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Video salient object detection(VSOD)aims at locating the most attractive objects in a video by exploring the spatial and temporal *** poses a challenging task in computer vision,as it involves processing complex spati...
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Video salient object detection(VSOD)aims at locating the most attractive objects in a video by exploring the spatial and temporal *** poses a challenging task in computer vision,as it involves processing complex spatial data that is also influenced by temporal *** the progress made in existing VSOD models,they still struggle in scenes of great background diversity within and between ***,they encounter difficulties related to accumulated noise and high time consumption during the extraction of temporal features over a long-term *** propose a multi-stream temporal enhanced network(MSTENet)to address these *** investigates saliency cues collaboration in the spatial domain with a multi-stream structure to deal with the great background diversity challenge.A straightforward,yet efficient approach for temporal feature extraction is developed to avoid the accumulative noises and reduce time *** distinction between MSTENet and other VSOD methods stems from its incorporation of both foreground supervision and background supervision,facilitating enhanced extraction of collaborative saliency *** notable differentiation is the innovative integration of spatial and temporal features,wherein the temporal module is integrated into the multi-stream structure,enabling comprehensive spatial-temporal interactions within an end-to-end *** experimental results demonstrate that the proposed method achieves state-of-the-art performance on five benchmark datasets while maintaining a real-time speed of 27 fps(Titan XP).Our code and models are available at https://***/RuJiaLe/MSTENet.
Unified programming models can effectively improve program portability on various heterogeneous high-performance *** unified programming models put a lot of effort to code portability but are still far from achieving ...
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Unified programming models can effectively improve program portability on various heterogeneous high-performance *** unified programming models put a lot of effort to code portability but are still far from achieving good performance *** this paper,we present a preliminary design of a performance-portable unified programming model including four aspects:programming language,programming abstraction,compilation optimization,and scheduling ***,domain-specific languages introduce domain knowledge to decouple the optimizations for different applications and *** unified programming abstraction unifies the common features of different architectures to support common ***-level compilation optimization enables comprehensive performance optimization based on multi-level intermediate ***-aware lightweight runtime scheduling system improves the resource utilization of heterogeneous *** is a perspective paper to show our viewpoints on programming models for emerging heterogeneous systems.
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