35,452 Result(s)
within
**hu Wang
Artificial Intelligence
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Article
ConDA: state-based data augmentation for context-dependent text-to-SQL
The context-dependent text-to-SQL task has profound real-world implications, as it facilitates users in extracting knowledge from vast databases, which allows users to acquire the information interactively for...
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A new uncertainty processing method for trajectory prediction
In many domains, trajectory prediction a crucial task. Uncertain information, such as complementary and correlated information between multiple features, complex interactive information, weather and temperatur...
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A general framework for improving cuckoo search algorithms with resource allocation and re-initialization
Cuckoo search (CS) has currently become one of the most favorable meta-heuristic algorithms (MHAs). In this article, a simple yet effective framework is proposed for CS algorithms to reinforce their performanc...
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Fast Shrinking parents-children learning for Markov blanket-based feature selection
High-dimensional data leads to degraded performance of machine learning algorithms and weak generalization of models, so feature selection is of great importance. In a Bayesian network (BN), the Markov blanket...
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Combining core points and cluster-level semantic similarity for self-supervised clustering
Contrastive learning utilizes data augmentation to guide network training. This approach has attracted considerable attention for clustering, object detection, and image segmentation. However, previous studies...
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Dual flow fusion graph convolutional network for traffic flow prediction
In recent decades, motor vehicle ownership has increased worldwide year by year, which causes that the accurate prediction of traffic flow on urban road networks becomes more important. However, the dual depen...
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TAENet: transencoder-based all-in-one image enhancement with depth awareness
Recently, CNN-based all-in-one image enhancement methods have been proposed to solve multiple image degradation tasks. However, these CNN-based methods usually have two limitations. One limitation is that they...
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Probabilistic load forecasting based on quantile regression parallel CNN and BiGRU networks
In the dynamic smart grid landscape, accurate probabilistic forecasting of electric load is critical. This paper presents a novel 24-hour-ahead probabilistic load forecasting model by integrating quantile regr...
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Dual stage black-box adversarial attack against vision transformer
Relying on wide receptive fields, Vision Transformers (ViTs) are more robust than Convolutional Neural Networks (CNNs). Consequently, some transfer-based attack methods that perform well on CNNs perform poorly...
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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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Novel multi-label feature selection via label enhancement and relative maximal discernibility pairs
Multi-label feature selection is an effective solution to the multi-label data dimensionality disaster problem. However, there are few studies on multi-label feature selection considering label enhancement met...
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Deep bilinear Koopman realization for dynamics modeling and predictive control
The data-driven approaches based on the Koopman operator theory have promoted the analysis and control of the nonlinear dynamics by providing an equivalent Koopman-based linear system associated with nonlinear...
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Article
Undersampling based on generalized learning vector quantization and natural nearest neighbors for imbalanced data
Imbalanced datasets can adversely affect classifier performance. Conventional undersampling approaches may lead to the loss of essential information, while oversampling techniques could introduce noise. To add...
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Real-time salient object detection based on accuracy background and salient path source selection
Boundary and connectivity prior are common methods for detecting the image salient object. They often address two problems: 1) if the salient object touches the image boundary, the saliency of the object will ...
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Article
Open AccessPinball-Huber boosted extreme learning machine regression: a multiobjective approach to accurate power load forecasting
Power load data frequently display outliers and an uneven distribution of noise. To tackle this issue, we present a forecasting model based on an improved extreme learning machine (ELM). Specifically, we intro...
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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...
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Topic-aware cosine graph convolutional neural network for short text classification
Graph Convolutional Network (GCN) has been extensively studied in the task of short text classification (STC), utilizing global graphs that incorporate texts at different levels of granularity to learn text em...
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Article
Transmission-guided multi-feature fusion Dehaze network
Image dehazing is an important direction of low-level visual tasks, and its quality and efficiency directly affect the quality of high-level visual tasks. Therefore, how to quickly and efficiently process hazy...
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Article
Block diagonal representation learning with local invariance for face clustering
Facial data under non-rigid deformation are often assumed lying on a highly non-linear manifold. The conventional subspace clustering methods, such as Block Diagonal Representation (BDR), can only handle the h...
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Multi-scale modeling to investigate the effects of transcranial magnetic stimulation on morphologically-realistic neuron with depression
Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique to activate or inhibit the activity of neurons, and thereby regulate their excitability. This technique has demonstrated pote...
