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Combining Image Space and q-Space PDEs for Lossless Compression of Diffusion MR Images
Diffusion MRI is a modern neuroimaging modality with a unique ability to acquire microstructural information by measuring water self-diffusion at the...
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A map**-based redirected walking algorithm for large-scale VR
In VR, the size mismatch between virtual and real space is one of the difficulties, so walking through a large-scale VR scene in a real small area...
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Research on performance optimization of virtual data space across WAN
For the high-performance computing in a WAN environment, the geographical locations of national supercomputing centers are scattered and the network...
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Multi-Scale Implicit Surface Reconstruction for Outdoor Scenes
The images used to reconstruct 3D models in outdoor scenes are generally captured at different scales. Accurately reconstructing geometry from...
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Large-Scale Agile
Large-scale agile development is required where time scales are short and the scope of work is, well, large. Large-scale development focuses on...
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Difference-guided multi-scale spatial-temporal representation for sign language recognition
Sign language recognition (SLR) is a challenging task, which requires a thorough understanding of spatial-temporal visual features for translating it...
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Enhancing surrogate-assisted evolutionary optimization for medium-scale expensive problems: a two-stage approach with unsupervised feature learning and Q-learning
This paper presents a novel two-stage progressive search approach with unsupervised feature learning and Q-learning (TSLL) to enhance...
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Semiotic Model of Mental Space
AbstractIt is proposed to consider a qualitative model of a person’s mental space as a decision support model. In contrast to the two-process model...
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Scale-Invariant Scale-Channel Networks: Deep Networks That Generalise to Previously Unseen Scales
The ability to handle large scale variations is crucial for many real-world visual tasks. A straightforward approach for handling scale in a deep...
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Large Scale Hypergraph Computation
As introduced in the previous chapters, the complexity of hypergraph computation is relatively high. In practical applications, the hypergraph may...
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Data augmentation based on shape space exploration for low-size datasets: application to 2D shape classification
This article introduces a novel 2D shape data augmentation approach based on intra-class shape space exploration. The proposed method relies on a...
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New proxemics in new space: proxemics in VR
With the development of computer technology, it is possible to design virtual reality (VR) media that provides services to multiple users. Hall’s...
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Indoor and Underground Space Measurement
Humans are good at exploiting the indoor and underground spaces to shelter themselves. Apart from open lands, indoor and underground spaces are...
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Face Super-Resolution via Progressive-Scale Boosting Network
Deep-learning-based face super-resolution (FSR) algorithms have performed more than traditional algorithms. However, existing methods need to pass...
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RMS-FlowNet++: Efficient and Robust Multi-scale Scene Flow Estimation for Large-Scale Point Clouds
The proposed RMS-FlowNet++ is a novel end-to-end learning-based architecture for accurate and efficient scene flow estimation that can operate on...
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GaitASMS: gait recognition by adaptive structured spatial representation and multi-scale temporal aggregation
Gait recognition is one of the most promising video-based biometric technologies. The edge of silhouettes and motion are the most informative feature...
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Real-time FPGA-based implementation of the AKAZE algorithm with nonlinear scale space generation using image partitioning
The first step in a scale invariant image matching system is scale space generation. Nonlinear scale space generation algorithms such as AKAZE,...
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Space to depth convolution bundled with coordinate attention for detecting surface defects
Surface defects of steel plates unavoidably exist during the industrial production proceeding due to the complex productive technologies and always...
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Large-Scale Entity Alignment
In this chapter, we focus on the concept of entity alignment at scale and present a new method for addressing this task. The proposed solution is...
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Evolutionary Machine Learning for Space
The Venn diagram of evolutionary computation, machine learning and space applications shows some intriguing overlaps. As evolutionary algorithms are...