2,411 Result(s)
within
**hu Li
Artificial Intelligence
Data Mining and Knowledge Discovery
Image Processing and Computer Vision
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Article
Open AccessRetraction Note: Using hardware counter-based performance model to diagnose scaling issues of HPC applications
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Retraction Note: Gray relational clustering model for intelligent guided monitoring horizontal wells
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Multi-scale deep echo state network for time series prediction
Echo state network (ESN) has widely attracted many researchers due to its training process without backpropagation. However, it is hard for single ESN to fit those complex and polytrophic situations. Under thi...
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Article
Correction to: HierMDS: a hierarchical multi-document summarization model with global–local document dependencies
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Article
Blockfd: blockchain-based federated distillation against poisoning attacks
Federated learning (FL) is a novel framework that distributes the model training to the participant devices to realize privacy-preserving machine learning. To achieve this, clients upload the parameters of the...
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Retraction Note: Fast and robust absolute camera pose estimation with known focal length
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TSCL-FHFN: two-stage contrastive learning and feature hierarchical fusion network for multimodal sentiment analysis
Multimodal sentiment analysis faces two challenges: modality representation and modality fusion. Most of the existing models rely only on the feature extraction network to learn modality representation, and th...
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Article
MultiPINN: multi-head enriched physics-informed neural networks for differential equations solving
Recently, the physics-informed neural network (PINN) has attracted much attention in solving partial differential equations (PDEs). The success is due to the strong generalization ability of the neural network...
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A coarse-to-fine small object detection framework based on a background complexity classification strategy
Object detection has achieved great progress and is used in various tasks. However, detecting small objects with lack of appearance information is still a challenging task. It is found that even if the trainin...
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Text-based person search by non-saliency enhancing and dynamic label smoothing
The current text-based person re-identification (re-ID) models tend to learn salient features of image and text, which however is prone to failure in identifying persons with very similar dress, because their ...
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Domain-invariant feature learning with label information integration for cross-domain classification
Traditional methods for unsupervised cross-domain classification learn a common low-dimensional subspace using images from a well-labeled source domain and an unlabeled target domain. To achieve domain-invaria...
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Ha-gnn: a novel graph neural network based on hyperbolic attention
Graph neural networks (GNNs) are powerful tools for data mining on graph-structured data in various domains, such as social science, finance, and biology. However, most existing GNNs operate in Euclidean space...
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Luminance domain-guided low-light image enhancement
Images captured under low-light conditions often suffer from low contrast, high noise, and uneven brightness due to nightlight, backlight, and shadow. These challenges make it difficult to use them as high-qua...
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An effective deep actor-critic reinforcement learning method for solving the flexible job shop scheduling problem
The flexible job shop scheduling problem (FJSP) is a classic NP-hard problem, and the quality of its scheduling solution directly affects the operational efficiency of the manufacturing system. However, the tr...
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EMARec: a sequential recommendation with exponential moving average
Capturing dynamic preference features from user historical behavioral data is widely applied to improve the accuracy of recommendations in sequential recommendation tasks. However, existing deep neural network...
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CSGAT-Net: a conditional pedestrian trajectory prediction network based on scene semantic maps and spatiotemporal graph attention
Pedestrian behavior exhibits high levels of dynamism, and pedestrian trajectories are influenced not only by the pedestrians themselves, but also by interactions with surrounding objects. Efficiently understan...
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Open AccessMulti-view GCN for loan default risk prediction
As a significant application of machine learning in financial scenarios, loan default risk prediction aims to evaluate the client’s default probability. However, most existing deep learning solutions treat eac...
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A two-stage dispatching approach for one-to-many ride-sharing with sliding time windows
Ride-sharing has transformed people’s travel habits with the development of various ride-sharing platforms, which can enhance the utilization of transportation resources, alleviate traffic congestion, and redu...
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Pose-aware video action segmentation
Action segmentation is an emerging task in video understanding, particularly for untrimmed videos containing multiple actions. However, existing video-based methods may struggle due to their sensitivity to vis...
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Prognosis prediction of high grade serous adenocarcinoma based on multi-modal convolution neural network
The prognostic analysis for high grade serous adenocarcinoma (HGSC) holds significant clinical importance. However, current prognostic analysis primarily relies on statistical techniques like logistic regressi...
