7,997 Result(s)
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Lu**g Sun
Artificial Intelligence
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Article
Cross-Modal Fusion and Progressive Decoding Network for RGB-D Salient Object Detection
Most existing RGB-D salient object detection (SOD) methods tend to achieve higher performance by integrating additional modules, such as feature enhancement and edge generation. There is no doubt that these mo...
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Article
Data-driven quantification and intelligent decision-making in traditional Chinese medicine: a review
Traditional Chinese medicine (TCM) originates from the practical experience of human beings’ constant struggle with nature. In five thousand years, TCM has gradually risen from empirical medicine to modern evi...
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Article
CMEFS: chaotic map**-based mayfly optimization with fuzzy entropy for feature selection
Swarm intelligence algorithms availably settle the issue of feature selection for classification, whereas the Mayfly Optimization Algorithm (MOA) proposed in recent years has the superiority of high precision,...
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Article
Model analysis and application case for complex multi-system evolutionary optimization
A complex system is made up of multiple related and coupled subsystems. Each subsystem has its own set of multiple constraints and objectives, and is commonly found in real-world applications. Biogeography-bas...
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Article
An evolutionary feature selection method based on probability-based initialized particle swarm optimization
Feature selection is a common data preprocessing technique that aims to construct better models by selecting the most predictive features. Existing particle swarm optimization-based feature selection algorithm...
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Article
Progressive image compression for Gaussian mixture model quartile intervals
In this paper, we proposed a novel deep image coding and decoding model for GMMQI (Gaussian mixture model quartile intervals, GMMQI) and a variable rate bit allocation method to optimize the rate distortion pe...
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Open AccessDynamic multi-label feature selection algorithm based on label importance and label correlation
Multi-label distribution is a popular direction in current machine learning research and is relevant to many practical problems. In multi-label learning, samples are usually described by high-dimensional featu...
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Article
SplatFlow: Learning Multi-frame Optical Flow via Splatting
The occlusion problem remains a crucial challenge in optical flow estimation (OFE). Despite the recent significant progress brought about by deep learning, most existing deep learning OFE methods still struggl...
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Hierarchical contrastive representation for zero shot learning
Zero-shot learning aims to identify unseen (novel) objects, using only labeled samples from seen (base) classes. Existing methods usually learn visual-semantic interactions or generate absent visual features o...
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De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network
Counterfactual inference for continuous rather than binary treatment variables is more common in real-world causal inference tasks. While there are already some sample reweighting methods based on Marginal Str...
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Article
Attention-based cross-frequency graph convolutional network for driver fatigue estimation
Fatigue driving significantly contributes to global vehicle accidents and fatalities, making driver fatigue level estimation crucial. Electroencephalography (EEG) is a proven reliable predictor of brain states...
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An enhanced teaching–learning-based optimization for the flexible job shop scheduling problem considering worker behaviours
In actual workshop scheduling, processing time is influenced by worker behaviours, such as learning, forgetting, fatigue and recovery. However, in the traditional workshop scheduling considering workers, these...
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Article
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 and cameras. With the widespread usage of deep models on hu...
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Open AccessA novel method for measuring center-axis velocity of unmanned aerial vehicles through synthetic motion blur images
Accurate velocity measurement of unmanned aerial vehicles (UAVs) is essential in various applications. Traditional vision-based methods rely heavily on visual features, which are often inadequate in low-light ...
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Deep learning-based classification and application test of multiple crop leaf diseases using transfer learning and the attention mechanism
Crop diseases are among the major natural disasters in agricultural production that seriously restrict the growth and development of crops, threatening food security. Timely classification, accurate identifica...
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Open AccessState-of-the-art review on the use of AI-enhanced computational mechanics in geotechnical engineering
Significant uncertainties can be found in the modelling of geotechnical materials. This can be attributed to the complex behaviour of soils and rocks amidst construction processes. Over the past decades, the f...
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Article
Open AccessKnowledge graph embedding closed under composition
Knowledge Graph Embedding (KGE) has attracted increasing attention. Relation patterns, such as symmetry and inversion, have received considerable focus. Among them, composition patterns are particularly import...
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Open AccessA comprehensive dataset for dynamic analysis of ocean front
This paper proposes an ocean front database and a method for its construction tailored for studying the dynamic evolution of ocean fronts. Ocean fronts play a crucial role in the interactions between the ocean...
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Retraction Note: Gray relational clustering model for intelligent guided monitoring horizontal wells
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Article
Towards effective urban region-of-interest demand modeling via graph representation learning
Identifying the region’s functionalities and what the specific Point-of-Interest (POI) needs is essential for effective urban planning. However, due to the diversified and ambiguity nature of urban regions, th...
