8,774 Result(s)
within
Chapter
Conference Paper
Lu**g Chen
English
Computer Communication Networks
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Chapter and Conference Paper
Practical Research on AI Visual Focus Analysis in Online Teaching
This project aims to study learners’ visual focus in online learning and their behavior patterns when engaging with different learning media and cognitive processes. It uses AI models and data analysis methods...
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Chapter and Conference Paper
MLDF-Net: Metadata Based Multi-level Dynamic Fusion Network
Computer-aided diagnosis has been widely used in the medical field, and one of the current research hotspots for aiding diagnosis is how to effectively fuse heterogeneous data such as image data and metadata. ...
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Chapter and Conference Paper
Research on Data Acquisition and Real-Time Communication for Intelligent Manufacturing Training Equipment Based on Model of Things and Intranet Penetration
Intelligent Manufacturing Training Equipment (IMTE) are featured with high-value shareable training property and high security requirement on human-machine interaction, which prompt urgent demands on equipment...
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Chapter and Conference Paper
Evolving Epidemic Management Rules Using Deep Neuroevolution: A Novel Approach to Inspection Scheduling and Outbreak Minimization
In epidemic management, the unpredictable dynamics of outbreaks, the constraints of available resources, and the complexity of variable interactions pose a significant challenge in designing effective manageme...
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Chapter and Conference Paper
A Cloud Computing User Experience Focused Load Balancing Method Based on Modified CMA-ES Algorithm
The development of the software and hardware has brought about the abundance and overflow of computing resources. Many Internet companies can lease idle computing resources based on the peak and valley cycles ...
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Chapter and Conference Paper
SD-Attack: Targeted Spectral Attacks on Graphs
Graph learning (GL) models have been applied in various predictive tasks on graph data. But, similarly to other machine learning models, GL models are also vulnerable to adversarial attacks. As a powerful atta...
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Chapter and Conference Paper
An Industrial Robot Path Planning Method Based on Improved Whale Optimization Algorithm
With the development of technology, robots are gradually being used more and more widely in various fields. Industrial robots need to perform path planning in the course of their tasks, but there is still a la...
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Chapter and Conference Paper
GraphNILM: A Graph Neural Network for Energy Disaggregation
Non-Intrusive Load Monitoring (NILM) remains a critical issue in both commercial and residential energy management, with a key challenge being the requirement for individual appliance-specific deep learning mo...
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Chapter and Conference Paper
Hybrid Encoded Attention Networks for Accurate Pulmonary Artery-Vein Segmentation in Noncontrast CT Images
Pulmonary artery-vein segmentation in computed tomography image is essential to lung disease diagnosis. It is still a challenge to segment small distal vessels, crossover and adhesion of arterioles due to comp...
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Chapter and Conference Paper
Heterogeneous Signcryption Scheme with Equality Test for Internet of Vehicles
By collecting and using vehicle dynamic data from sensors on vehicles, Internet of Vehicles (IoV) has greatly enhanced the convenience and intelligence of users’ transportation. However, the data transmission ...
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Chapter and Conference Paper
Multimodal Rumor Detection by Using Additive Angular Margin with Class-Aware Attention for Hard Samples
Currently, several factors limit the practicality of multimodal rumor detection (MRD). These include incomplete feature fusion in multimodal data, the weak discriminative power in the softmax-based loss, and t...
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Chapter and Conference Paper
An Improved Trajectory Planning Method for Unmanned Aerial Vehicles in Complex Environments
Trajectory planning plays a crucial role in the execution of Unmanned aerial vehicle (UAV) missions. However, planning an optimal collision-free trajectory is a challenging task, especially in complex environm...
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Chapter and Conference Paper
A Study of the Impact of Different Teaching Methods on Students’ Learning in Design Thinking Courses in Taiwan
This study explores the landscape of design thinking courses in Taiwan, focusing on 50 relevant courses and identifying four primary teaching methods: Experiential Learning, Active Learning, Learning by Teachi...
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Chapter and Conference Paper
Q-TrHDRI: A Qurey-Based Transformer for High Dynamic Range Imaging with Dynamic Scenes
In the absence of well-exposed contents in images, high dynamic range image (HDRI) provides an attractive option that fuses stacked low dynamic range (LDR) images into an HDR image. Existing HDRI methods utili...
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Chapter and Conference Paper
A Blockchain-Based Proxy Re-Encryption Scheme with Cryptographic Reverse Firewall for IoV
As the Internet of vehicles (IoV) technology develops, it promotes the intelligent interaction among vehicles, road side instrument, and the environment. Nevertheless, it also brings vehicle information securi...
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Chapter and Conference Paper
MARS: An Instance-Aware, Modular and Realistic Simulator for Autonomous Driving
Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely recognized that realistic sensor simulation will play a critical role in solving remaining corner cases by simulating them. To t...
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Chapter and Conference Paper
Maximum Fairness-Aware (k, r)-Core Identification in Large Graphs
Cohesive subgraph mining is a fundamental problem in attributed graph analysis. The k-core model has been widely used in many studies to measure the cohesiveness of subgraphs. However, none of them considers the ...
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Chapter and Conference Paper
Learning Local Features of Motion Chain for Human Motion Prediction
Extracting local features is a key technique in the field of human motion prediction. However, Due to incorrect partitioning of strongly correlated joint sets, existing methods ignore parts of strongly correla...
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Chapter and Conference Paper
Prudent Promotion, Steady Development: Capability and Safety Considerations for Applying Large Language Models in Medicine
The powerful capabilities of large language models (LLMs) in the medical field have been affirmed by various benchmark tests. However, safety assessments are indispensable for high-risk medical applications. W...
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Chapter and Conference Paper
A Novel Semi-supervised IoT Time Series Anomaly Detection Model Using Graph Structure Learning
Internet of Things (IoT) is an evolving paradigm for building smart cross-industry. The data gathered from IoT devices may have anomalies or other errors for various reasons, such as malicious activities or se...
