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An innovative fourth-order numerical scheme with error analysis for Lane-Emden-Fowler type systems
In this paper, we develop a novel higher-order compact finite difference scheme for solving systems of Lane-Emden-Fowler type equations. Our method...
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Explicit constructions of NMDS self-dual codes
Near maximum distance separable (NMDS) codes are important in finite geometry and coding theory. Self-dual codes are closely related to...
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Sublinear Algorithms in T-Interval Dynamic Networks
We consider standard T - interval dynamic networks , under the synchronous timing model and the broadcast CONGEST model. In a T - interval dynamic network ,...
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Learning to sculpt neural cityscapes
We introduce a system that learns to sculpt 3D models of massive urban environments. The majority of humans live their lives in urban environments,...
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M2AST:MLP-mixer-based adaptive spatial-temporal graph learning for human motion prediction
Human motion prediction is a challenging task in human-centric computer vision, involving forecasting future poses based on historical sequences....
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Unconditional energy stability and maximum principle preserving scheme for the Allen-Cahn equation
In this paper, we propose a novel fully implicit numerical scheme that satisfies both nonlinear energy stability and maximum principle for the space...
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A full-detection association tracker with confidence optimization for real-time multi-object tracking
Multi-object tracking (MOT) aims to obtain trajectories with unique identifiers for multiple objects in a video stream. In current approaches,...
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ACL-SAR: model agnostic adversarial contrastive learning for robust skeleton-based action recognition
Human skeleton data have been widely explored in action recognition and the human–computer interface recently, thanks to off-the-shelf motion sensors...
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Global adaptive histogram feature network for automatic segmentation of infection regions in CT images
Accurate and timely diagnosis of COVID-like virus is of paramount importance for lifesaving. In this work, deep learning techniques are applied to...
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Fractional Legendre wavelet approach resolving multi-scale optimal control problems involving Caputo-Fabrizio derivative
This article provides an effective numerical approach using the fractional integral operational matrix method for a fractional Legendre wavelet to...
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Unconditionally positivity-preserving approximations of the Aït-Sahalia type model: Explicit Milstein-type schemes
The present article aims to design and analyze efficient first-order strong schemes for a generalized Aït-Sahalia type model arising in mathematical...
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Smart contract vulnerabilities detection with bidirectional encoder representations from transformers and control flow graph
Up to now, the smart contract vulnerabilities detection methods based on sequence modal data and sequence models have been the most commonly used....
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Real-time and secure identity authentication transmission mechanism for artificial intelligence generated image content
The rapid development of generative artificial intelligence technology and large-scale pre-training models has led to the emergence of artificial...
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Intersecting realms: a cross-disciplinary examination of VR quality of experience research
The advent of virtual reality (VR) technology has necessitated a reevaluation of quality of experience (QoE) models. While numerous recent efforts...
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Continual few-shot patch-based learning for anime-style colorization
The automatic colorization of anime line drawings is a challenging problem in production pipelines. Recent advances in deep neural networks have...
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Error analysis of a high-order fully discrete method for two-dimensional time-fractional convection-diffusion equations exhibiting weak initial singularity
This study presents a novel high-order numerical method designed for solving the two-dimensional time-fractional convection-diffusion (TFCD)...
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Autocleandeepfood: auto-cleaning and data balancing transfer learning for regional gastronomy food computing
Food computing has emerged as a promising research field, employing artificial intelligence, deep learning, and data science methodologies to enhance...
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A novel single kernel parallel image encryption scheme based on a chaotic map
The development of communication technologies has increased concerns about data security, increasing the prominence of cryptography. Images are one...
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Usability of visualizing position and orientation deviations for manual precise manipulation of objects in augmented reality
Manual precise manipulation of objects is an essential skill in everyday life, and Augmented Reality (AR) is increasingly being used to support such...