229 Result(s)
within
Chapter
Minghui **ao
Computer Science
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Chapter and Conference Paper
Ensemble of Randomized Neural Network and Boosted Trees for Eye-Tracking-Based Driver Situation Awareness Recognition and Interpretation
Ensuring traffic safety is crucial in the pursuit of sustainable transportation. Across diverse traffic systems, maintaining good situation awareness (SA) is important in promoting and upholding traffic safety...
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Chapter and Conference Paper
Dynamic Graph-Driven Heat Diffusion: Enhancing Industrial Semantic Segmentation
Dust significantly impacts construction progress and worker health, necessitating the use of machine learning for dust area identification and pollution mitigation. Existing dust semantic segmentation methods ...
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Chapter and Conference Paper
AgsNet: An Attention-Guided Lightweight Segmentation Network
Urinalysis test strips are commonly used for urine routine examination. However, due to possible defects in the liquid path, such as blockages, droplets may leak during the process of drop** urine samples on...
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Chapter and Conference Paper
Deep Neural Network Model over Encrypted Data
Deep Neural Networks (DNN) model training usually requires a large amount of data as the foundation, so that the model can learn effective features and rules. However, these data often contain sensitive inform...
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Chapter and Conference Paper
Construction of Multimodal Dialog System via Knowledge Graph in Travel Domain
When traveling to a foreign city, we often find ourselves in dire need of an intelligent agent that can provide instant and informative responses to our various queries. Such an agent should have the ability t...
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Chapter and Conference Paper
MixCL: Mixed Contrastive Learning for Relation Extraction
Entity representation plays a fundamental role in modern relation extraction models. Previous efforts usually explicitly distinguish entities from contextual words, e.g., by introducing position embedding w.r....
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Chapter and Conference Paper
Learning Discriminative Semantic and Multi-view Context for Domain Adaptive Few-Shot Relation Extraction
Few-shot relation extraction enables the model to extract new relations and achieve impressive success. However, when new relations come from new domains, semantic and syntactic differences cause a dramatic dr...
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Chapter
Learning-Based Resource Management for Maritime Communications
With the booming smart maritime services from IoT devices, located in the underwater vehicles, ships, sensors and underwater industrial the 5G networks that have supported industrial automation in Palattella e...
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Chapter
Learning-Based Intelligent Reflecting Surface-Aided Secure Maritime Communications
Physical layer security (PLS) has attracted increasing attention as an alternative to cryptography-based techniques for maritime wireless communications (Liu et al., IEEE J. Sel. Areas Commun. 39(10), 2992–3005 (...
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Chapter
Conclusions and Future Work
In this book, we have discussed maritime communications based on RL to enhance reliability and security performance, including IRS-aided communications, privacy-aware IoT communications, intelligent resource m...
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Chapter and Conference Paper
HuMoMM: A Multi-Modal Dataset and Benchmark for Human Motion Analysis
Human motion analysis is a fundamental task in computer vision, and there is an increasing demand for versatile datasets with the development of deep learning. However, how to obtain the annotations of human m...
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Chapter
Learning-Based Maritime Location Privacy Protection
In maritime networks (MNs), ships and other maritime mobile devices release their geographical and semantic information of the visited places (e.g., harbors, passenger terminals, and oil terminals) to request ...
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Chapter and Conference Paper
Recurrent Transformers for Long Document Understanding
Pre-trained models have been proved effective in natural language understanding. For long document understanding, the key challenges are long-range dependence and inference efficiency. Existing approaches, how...
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Chapter and Conference Paper
CARL: Cross-Aligned Representation Learning for Multi-view Lung Cancer Histology Classification
Accurately classifying the histological subtype of non-small cell lung cancer (NSCLC) using computed tomography (CT) images is critical for clinicians in determining the best treatment options for patients. Al...
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Chapter and Conference Paper
Semantic Difference Guidance for the Uncertain Boundary Segmentation of CT Left Atrial Appendage
Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, which is closely relevant to anatomical structures including the left atrium (LA) and the left atrial appendage (LAA). Thus, a th...
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Chapter and Conference Paper
Meta-learning Siamese Network for Few-Shot Text Classification
Few-shot learning has been used to tackle the problem of label scarcity in text classification, of which meta-learning based methods have shown to be effective, such as the prototypical networks (PROTO). Despi...
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Chapter
Introduction
Maritime communication systems have attracted ever-increasing research attention and become an important part of the fifth-/sixth-generation (5G/6G) communications. Maritime communication networks support ship...
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Chapter
Learning-Based Privacy-Aware Maritime IoT Communications
Mobile edge computing helps maritime IoT devices with energy harvesting to provide satisfactory experiences for computation-intensive applications in maritime communication systems, such as real-time cargo sta...
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Chapter and Conference Paper
X-shape Feature Expansion Network for Salient Object Detection in Optical Remote Sensing Images
Salient object detection in optical remote sensing images (RSI-SOD) is a valuable and challenging task. Some factors in RSI, such as the extreme complexity of scale and topological structure as well as the unc...
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Chapter and Conference Paper
FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation
Cross-silo federated learning (FL) enables the development of machine learning models on datasets distributed across data centers such as hospitals and clinical research laboratories. However, recent research ...
