50 Result(s)
within
**bin Guo
Computer Science
English
Computer Communication Networks
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Chapter and Conference Paper
A Novel Framework for Adaptive Quadruped Robot Locomotion Learning in Uncertain Environments
Learning diverse and flexible locomotion strategies in uncertain environments has been a longstanding challenge for quadruped robots. Although recent progress in domain randomization has partially tackled this...
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Chapter and Conference Paper
Autonomous Communication Decision Making Based on Graph Convolution Neural Network
As a method of multi-agent system cooperation, multi-agent communication can help agents negotiate and adjust behavior decisions by exchanging information such as observation, intention, or experience during o...
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Article
Retraction Note: Cloud platform wireless sensor network detection system based on data sharing
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Chapter and Conference Paper
Aesthetics-Diven Online Summarization to First-Person Tourism Videos
Nowadays video blog (vlog) has gradually become popular. In scenarios such as tourism, many vloggers use mobile terminals to record first-person videos, which have redundant information, complex scenes and con...
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Chapter
Mobile Crowdsourcing Task Offloading on Social Collaboration Networks: An Empirical Study
Mobile Crowdsourcing (MCS), a human-centric promising paradigm for performing location-based tasks, has drawn rising attention from both academia and industry. In MCS applications, the outsourced tasks are all...
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Chapter and Conference Paper
Visual Scene-Aware Dialogue System for Cross-Modal Intelligent Human-Machine Interaction
Adequate perception and understanding of the user’s visual context is an important part of a robot’s ability to interact naturally with humans and achieve true anthropomorphism. In this paper, we focus on the ...
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Chapter and Conference Paper
Scene Adaptive Persistent Target Tracking and Attack Method Based on Deep Reinforcement Learning
As an intelligent device integrating a series of advanced technologies, mobile robots have been widely used in the field of defense and military affairs because of their high degree of autonomy and flexibility...
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Chapter and Conference Paper
Attention Skip Connection Dense Network for Accurate Iris Segmentation
As a key step in the iris recognition process, iris segmentation directly affects the accuracy of iris recognition. How to achieve accurate iris segmentation under various environmental conditions is a big cha...
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Chapter and Conference Paper
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
Federated learning (FL) is an emerging distributed machine learning paradigm that avoids data sharing among training nodes so as to protect data privacy. Under the coordination of the FL server, each client co...
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Chapter and Conference Paper
How Metacognitive Monitoring Feedback Influences Workload in a Location-Based Augmented Reality Environment
This research aims to investigate the impact on workload caused by metacognitive monitoring feedback (MCMF) in a location-based augmented reality (AR) learning environment. MCMF helps learners to monitor and c...
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Chapter and Conference Paper
Complex Task Allocation in Spatial Crowdsourcing: A Task Graph Perspective
In this paper, we study a novel spatial crowdsourcing scenario, where a complex outsourced task is divided into a group of subtasks with dependency relationships. Under this scenario, we investigate a Task Graph
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Chapter and Conference Paper
Constructing Knowledge Graph for Prognostics and Health Management of On-board Train Control System Based on Big Data and XGBoost
Train control system plays a significant role in safe and efficient operation of the railway transport system. In order to enhance the system capability and cost efficiency from a full life cycle perspective, ...
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Article
High-efficiency face detection and tracking method for numerous pedestrians through face candidate generation
This paper is dedicated to develo** high-efficiency face detection and tracking method for big dynamic crowds or numerous pedestrians. Three modules constitute the proposed method, i.e., face candidate gener...
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Article
Single image super-resolution via low-rank tensor representation and hierarchical dictionary learning
Super-resolution (SR) has been widely studied due to its importance in real applications and scenarios. In this paper, we focus on generating an SR image from a single low-resolution (LR) input image by employ...
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Chapter and Conference Paper
Mining Network Security Holes Based on Data Flow Analysis in Smart Grid
With the popularity of mobile terminals and the sharp increase in network data traffic, the problem of security loopholes has become increasingly prominent. The traditional vulnerability detection methods can ...
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Chapter and Conference Paper
Research on OTFS Performance Based on Joint-Sparse Fast Time-Varying Channel Estimation
Contraposing the problem of high pilot overhead and poor estimation performance for OFDM system in fast time-varying channels, a novel channel estimation method based on joint-sparse basis expansion model is p...
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Chapter and Conference Paper
Interpretable Multivariate Time Series Classification Based on Prototype Learning
Recently, the classification of multivariate time series has attracted much attention in the field of machine learning and data mining, due to its wide application values in biomedicine, finance, industry and ...
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Chapter and Conference Paper
MateBot: The Design of a Human-Like, Context-Sensitive Virtual Bot for Harmonious Human-Computer Interaction
The virtual bot is one of the hot topics in artificial intelligence, where most of the current studies focus on chatbots. Nevertheless, the context-sensitive virtual bot, especially with rich human-like intera...
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Chapter and Conference Paper
Over-Smoothing Algorithm and Its Application to GCN Semi-supervised Classification
The feature information of the local graph structure and the nodes may be over-smoothing due to the large number of encodings, which causes the node characterization to converge to one or several values. In ot...
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Chapter and Conference Paper
MGCN4REC: Multi-graph Convolutional Network for Next Basket Recommendation with Instant Interest
Sequential patterns involved in users’ historical behaviors have received extensive attention in recommendation system, which is important to represent item-level preferences. The existing works often combine ...
