This paper aims to build an efficient multi-dimensional visualization platform for GIS landscape data. Through this system, large-scale, multi-type landscape data in the geographic information system can be automatica...
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Story visualization is the transformation of narrative elements into image sequences. While existing research has primarily focused on visual contextual coherence, the deeper narrative essence of stories often remains...
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This article proposes a multi-level 3D visualization monitoring technology based on digital twins. Through digital twin technology, we need to simulate laboratory environments, monitor and analyze various parameters i...
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This paper proposes a design for a visualization system for underwater multi-target tracking based on the Gaussian Mixture Probability Hypothesis Density (GMPHD) filter using Unity 3D engine. Traditional analysis meth...
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Emotional information in narrative texts is an important resource for deepening text interpretation and promoting literature utilization, but there is still a lack of dedicated information organization schemes. Based ...
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Text-to-visualization (Text2Vis) aims to democratize data insights for non-expert users by transforming natural language query (NLQ) into visualization specification (VS). In view of the high dependence of rule-based ...
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Planning land use changes requires input from experts across several domains with diverse expertise. Currently available tools were not designed for analysing the required ecosystem services before and after land use ...
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On account of the extreme settings, stealing the black-box model without its training data is difficult in practice. On this topic, along the lines of data diversity, this paper substantially makes the following impro...
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On account of the extreme settings, stealing the black-box model without its training data is difficult in practice. On this topic, along the lines of data diversity, this paper substantially makes the following improvements based on our conference version (dubbed STDatav1, short for Surrogate Training Data). First, to mitigate the undesirable impacts of the potential mode collapse while training the generator, we propose the joint-data optimization scheme, which utilizes both the synthesized data and the proxy data to optimize the surrogate model. Second, we propose the self-conditional data synthesis framework, an interesting effort that builds the pseudo-class mapping framework via grouping class information extraction to hold the class-specific constraints while holding the diversity. Within this new framework, we inherit and integrate the class-specific constraints of STDatav1 and design a dual cross-entropy loss to fit this new framework. Finally, to facilitate comprehensive evaluations, we perform experiments on four commonly adopted datasets, and a total of eight kinds of models are employed. These assessments witness the considerable performance gains compared to our early work and demonstrate the competitive ability and promising potential of our approach.
With the increasing requirements for power supply systems and the continuous improvement of emergency rescue command center system construction, the requirements for early warning emergency systems are constantly incr...
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Narrow Band Imaging (NBI) is an optical medical imaging technique that utilizes narrow band light to enhance the visualization of mucosa and tissues. NBI has been used to enhance traditional white light endoscopic ima...
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