406 Result(s)
within
**g-** Ge
Computer Science
English
Data Mining and Knowledge Discovery
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Article
Multi-factor stock price prediction based on GAN-TrellisNet
Applying deep learning, especially time series neural networks, to predict stock price, has become one of the important applications in quantitative finance. Recently, some GAN-based stock prediction models ar...
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Article
Micro drill defect detection with hybrid BP networks, clusters selection and crossover
According to the solution requirements, linear BP neural networks are designed which are consistent with the feature curves of the fitted equation, when the neural networks reach the equilibrium and stable sta...
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Article
Open AccessLeveraging Semantic Information for Enhanced Community Search in Heterogeneous Graphs
Community search (CS) is a vital research area in network science that focuses on discovering personalized communities for query vertices from graphs. However, existing CS methods mainly concentrate on homogen...
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Article
PCDR-DFF: multi-modal 3D object detection based on point cloud diversity representation and dual feature fusion
Recently, multi-modal 3D object detection techniques based on point clouds and images have received increasing attention. However, existing methods for multi-modal feature fusion are often relatively singular,...
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Article
Open AccessEstablishment of an automatic diagnosis system for corneal endothelium diseases using artificial intelligence
To use artificial intelligence to establish an automatic diagnosis system for corneal endothelium diseases (CEDs).
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Article
Open AccessMCAD: Multi-classification anomaly detection with relational knowledge distillation
With the wide application of deep learning in anomaly detection (AD), industrial vision AD has achieved remarkable success. However, current AD usually focuses on anomaly localization and rarely investigates a...
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Article
Correction: GAL: combining global and local contexts for interpersonal relation extraction toward document-level Chinese text
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Article
GAL: combining global and local contexts for interpersonal relation extraction toward document-level Chinese text
Current interpersonal relation extraction toward Chinese text remains at the sentence-level, which narrows practical applications since most relational facts are implied through multiple sentences in the docum...
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Article
Neighborhood rough set with neighborhood equivalence relation for feature selection
Feature selection of the neighborhood rough set is an important step in preprocessing the data and improving classification performance. Neighborhood granules form the basis for neighborhood rough set learning...
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Article
Finite-time adaptive fuzzy control of nonlinear systems with actuator faults and input saturation
This paper addresses the finite-time control problem of a class of uncertain nonlinear systems subject to input saturation and actuator faults. To approximate the unknown system states, a fuzzy state observer ...
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Chapter and Conference Paper
Efficient Attention for Domain Generalization
Deep neural networks suffer severe performance degradation when encountering domain shift. Previous methods mainly focus on feature manipulation in source domains to learn transferable features to unseen domai...
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Chapter and Conference Paper
Interactive Selection Recommendation Based on the Multi-head Attention Graph Neural Network
The click-through rate prediction of users is a critical task in the recommendation system. As a powerful machine learning method, graph neural networks have been favored by scholars to solve the task recently...
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Chapter and Conference Paper
GenRec: Large Language Model for Generative Recommendation
In recent years, Large Language Models (LLMs) have emerged as powerful tools for diverse natural language processing tasks. However, their potential for recommender systems under the generative recommendation ...
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Chapter and Conference Paper
How Legal Knowledge Graph Can Help Predict Charges for Legal Text
The existing methods for predicting Easily Confused Charges (ECC) primarily rely on factual descriptions from legal cases. However, these approaches overlook some key information hidden in these descriptions, ...
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Chapter and Conference Paper
Research on Control of Virtual and Real Drive System of Intelligent Factory Robot Based on Digital Twin
Traditional virtual and real robot drive systems use management methods, but due to the impact of the production environment, the system’s command response speed is slow, which affects the control effect. To a...
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Chapter and Conference Paper
Attribution of Adversarial Attacks via Multi-task Learning
Deep neural networks (DNNs) can be easily fooled by adversarial examples during inference phase when attackers add imperceptible perturbations to original examples. Many works focus on adversarial detection an...
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Chapter and Conference Paper
Neural Networks in Forecasting Financial Volatility
In 2020s, the state of the art (SOTA) in financial volatility forecasting is underpinned by deep learning (DL). Despite this, forecasting methods in practice tend to be dominated by their more traditional coun...
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Chapter and Conference Paper
Empowering Legal Citation Recommendation via Efficient Instruction-Tuning of Pre-trained Language Models
The escalating volume of cases in legal adjudication has amplified the complexity of citing relevant regulations and authoritative cases, posing an increasing challenge for legal professionals. Current legal c...
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Chapter and Conference Paper
Tool Condition Monitoring and Maintenance Based on Deep Reinforcement Learning
Tool status monitoring requires collecting a large amount of data to complete analysis, and different types of tools may exhibit different wear and failure modes during processing, making tool status monitorin...
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Chapter and Conference Paper
Continual Few-Shot Relation Extraction with Prompt-Based Contrastive Learning
Continual relation extraction (CRE) aims to continually learn new relations while maintaining knowledge of previous relations in the data streams. Recently, continual few-shot relation extraction (CFRE) is int...
