6,144 Result(s)
within
English
Computer Science
Artificial Intelligence
Computer Communication Networks
**mo Wang
Chapter
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Chapter
Conclusion and Future Directions
In previous chapters, we have presented our observations and results on mobile data dynamics in heterogeneous wireless networks, from four aspects: the cause, description, governing rule, and impact, respectiv...
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Chapter and Conference Paper
A Robust Detection and Correction Framework for GNN-Based Vertical Federated Learning
Graph Neural Network based Vertical Federated Learning (GVFL) facilitates data collaboration while preserving data privacy by learning GNN-based node representations from participants holding different dimensi...
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Chapter
Introduction
Data, which refers to transmittable and storable computer information, has been an integral part of modern society ever since the invention of computers. Especially in the past decade, its indispensable role in v...
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Chapter
Coverage Dynamics: Modeling and Analysis of Data Coverage in Heterogeneous Edge Networks
Our study in the previous chapter revealed the lifetime of mobile data in large networks, to address the when question. In this chapter, we shift gear to another important aspect of mobile data, that is, the wher...
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Chapter
Spectrum Dynamics: Modeling, Analysis, and Design of Spectrum Activity Surveillance in DSA-Enabled Systems
In the previous chapter, we discussed the impact on network resource by data movements in the offloading process, but it is still not clear how to observe such impact. This is especially true for the spectrum res...
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Chapter and Conference Paper
Zero-Shot Medical Information Retrieval via Knowledge Graph Embedding
In the era of the Internet of Things (IoT), the retrieval of relevant medical information has become essential for efficient clinical decision-making. This paper introduces MedFusionRank, a novel approach to z...
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Chapter and Conference Paper
Dual-Stream Context-Aware Neural Network for Survival Prediction from Whole Slide Images
Whole slide images (WSI) encompass a wealth of information about the tumor micro-environment, which holds prognostic value for patients’ survival. While significant progress has been made in predicting patient...
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Chapter and Conference Paper
Classification Method for Ship-Radiated Noise Based on Joint Feature Extraction
In order to address the problem of poor recognition performance from single signal features in ship identification and to enhance the accuracy of Convolutional Neural Networks (CNNs) in underwater acoustic tar...
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Chapter and Conference Paper
User-Aware Prefix-Tuning Is a Good Learner for Personalized Image Captioning
Image captioning bridges the gap between vision and language by automatically generating natural language descriptions for images. Traditional image captioning methods often overlook the preferences and charac...
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Chapter
Information Dynamics: Modeling and Analysis of Conflicting Information Propagation in a Finite Time Horizon
Information propagation is the driving force of mobile data dynamics. In this chapter, we study information dynamics, particularly the propagation process of conflicting information in networks, to provide in-...
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Chapter
Governing Rules: Modeling and Analysis of Task Offloading Processes in the Fog
In the previous chapters, we discussed the dissemination process of one data block, particularly its lifetime and whereabouts, in wireless networks. As data services quickly migrate to the network edge, which is ...
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Chapter and Conference Paper
Decoupled Contrastive Learning for Long-Tailed Distribution
Self-supervised contrastive learning is popularly used to obtain powerful representation models. However, unlabeled data in the real world naturally exhibits a long-tailed distribution, making the traditional ...
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Chapter and Conference Paper
Correction to: A Survey of Control Flow Graph Recovery for Binary Code
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Chapter and Conference Paper
Distributional Kernel: An Effective and Efficient Means for Trajectory Retrieval
In this paper, we propose a new and powerful way to represent trajectories and measure the distance between them using a distributional kernel. Our method has two unique properties: (i) the identity property w...
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Chapter and Conference Paper
Event Sparse Net: Sparse Dynamic Graph Multi-representation Learning with Temporal Attention for Event-Based Data
Graph structure data has seen widespread utilization in modeling and learning representations, with dynamic graph neural networks being a popular choice. However, existing approaches to dynamic representation ...
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Chapter and Conference Paper
Knowledge Graph Reasoning with Bidirectional Relation-Guided Graph Attention Network
Graph convolutional neural networks (GCN) have demonstrated superior performance in graph data modeling and have been widely used in knowledge inference research in recent years. However, knowledge graph is a ...
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Chapter and Conference Paper
Learning Bottleneck Transformer for Event Image-Voxel Feature Fusion Based Classification
Recognizing target objects using an event-based camera draws more and more attention in recent years. Existing works usually represent the event streams into point-cloud, voxel, image, etc., and learn the feat...
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Chapter and Conference Paper
Sequence-Based Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing: A Comparison Study
Mobile edge computing aims to extend cloud services to the network edge, thereby reducing the computational burden on mobile devices and enabling even simple devices to perform computationally intensive tasks ...
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Chapter and Conference Paper
Prediction of Rice Processing Loss Rate Based on GA-BP Neural Network
Food is closely related to national economy and people’s livelihood. Rice is the largest grain crop in China, it is crucial to predict the loss rate of rice during processing to reduce food waste and ensure fo...
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Chapter and Conference Paper
A Pixel-Level Segmentation Method for Water Surface Reflection Detection
Water surface reflections pose challenges to unmanned surface vehicles or robots during target detection and tracking tasks, leading to issues such as the loss of tracked targets and false target detection. Cu...
