209 Result(s)
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English
Artificial Intelligence
Computer Systems Organization and Communication Networks
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Chapter
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Chapter and Conference Paper
IoT Botnet Attacks Detection and Classification Based on Ensemble Learning
With the vigorous development of the IoT, botnet attacks against the IoT have become more frequent and diverse, and the research on attack prevention and detection has become more difficult. This paper propose...
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Chapter and Conference Paper
MTMG: A Framework for Generating Adversarial Examples Targeting Multiple Learning-Based Malware Detection Systems
As machine learning technology continues to advance rapidly, an increasing number of researchers are utilizing it in the field of malware detection. Despite the fact that learning-based malware detection syste...
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Chapter and Conference Paper
Context-Aware Automatic Splitting Method for Structured Complex Crowdsourcing Tasks
Crowdsourcing as a practical way of ensuring data quality has achieved great success in fields like image annotation, speech recognition, etc. For structured complex tasks like translation which are usually ve...
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Chapter and Conference Paper
Unsupervised Contrastive Learning of Sentence Embeddings Through Optimized Sample Construction and Knowledge Distillation
Unsupervised contrastive learning of sentence embedding has been a recent focus of researchers. However, issues such as unreasonable division of positive and negative samples and poor data enhancement leading ...
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Chapter and Conference Paper
Self-agreement: A Framework for Fine-Tuning Language Models to Find Agreement Among Diverse Opinions
Finding an agreement among diverse opinions is a challenging topic in social intelligence. Recently, large language models (LLMs) have shown great potential in addressing this challenge due to their remarkable...
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Chapter and Conference Paper
A Deep Reinforcement Learning Based Facilitation Agent for Consensus Building Among Multi-Round Discussions
Achieving consensus among diverse opinions through multi-round discussions can be a complex process. The advent of large language models (LLMs) offers promising avenues for resolving this challenge, given thei...
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Chapter and Conference Paper
MARL \(_{4}DRP\) : Benchmarking Cooperative Multi-agent Reinforcement Learning Algorithms for Drone Routing Problems
The use of drones as an efficient delivery solution is a promising technology, addressing the growing demand for deliveries. Unlike the traditional vehicle routing problem (VRP), we introduce a new drone routi...
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Chapter and Conference Paper
A Quantitative Evaluation Method for Parkinson's Disease
Objective, quantifiable, and easy to operate evaluation methods are crucial for assisting in the diagnosis of Parkinson's disease. In the widely used Unified Parkinson's Disease Rating Scale (UPDRS) III, item ...
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Chapter and Conference Paper
Semantic Segmentation of Remote Sensing Architectural Images Based on GAN and UNet3+ Model
Semantic segmentation of remote sensing building images can provide important data support for urban planning and resource management. It also plays a crucial role in assessing building density, monitoring urb...
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Chapter and Conference Paper
Distributed Dynamic Process Monitoring Based on Maximum Correlation and Maximum Difference
In order to solve the problem of dynamic characteristics caused by the autocorrelation of different measurement variables and the cross-correlation of variables reflected at different sampling times in industr...
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Chapter and Conference Paper
A Reinforcement Learning Approach for Personalized Diversity in Feeds Recommendation
Feeds recommendation has been widely used in various applications, such as e-commerce site, where users can constantly browse products generated by never-ending feeds. It’s important to not only consider insta...
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Chapter and Conference Paper
Seamless Integration of Efficient 6G Wireless Technologies for Communication and Sensing Enabling Ecosystems
The vision of 6G foresees telecommunication infrastructures that move from provisioning classical telecommunication and data services to delivering more intelligent, flexible and energy-aware services, opening...
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Chapter and Conference Paper
DQN-Based Comprehensive Consumption Minimization on Calculation Offloading in Mobile Edge Computing
When Internet of Things (IoT) devices similar to sensors collect and analyze information outdoors, they often encounter insufficient energy or information cannot be analyzed in time. To make sensor devices wor...
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Chapter and Conference Paper
Stochastic Task Offloading Problems for Edge Computing
The edge-cloud computing is extensively deployed to provide convenient computing.
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Chapter and Conference Paper
Effectiveness of Malicious Behavior and Its Impact on Crowdsourcing
Crowdsourcing has achieved great success in fields like data annotation, social survey, objects labeling, etc. However, enticed by potential high rewards, we have seen more and more malicious behavior like pla...
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Chapter and Conference Paper
BusWTE: Realtime Bus Waiting Time Estimation of GPS Missing via Multi-task Learning
Realtime bus waiting time is of great importance to the intelligent public transportation system and is beneficial for improving user satisfaction by online map services. While there are limited realtime bus w...
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Chapter and Conference Paper
DLUIO: Detecting Useful Investor Opinions by Deep Learning
In recent years, due to the increasing popularity of investment microblogging platforms (e.g., Stocktwits), a critical challenge is to detect useful investor opinions and use them to make wise trading decision...
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Chapter and Conference Paper
Dependency-Based Task Assignment in Spatial Crowdsourcing
Task assignment is one of the central problems in spatial crowdsourcing research. A good assignment approach will match the best performer to the task. Complex tasks account for an increasing proportion of tas...
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Chapter and Conference Paper
A Cuboid Volume Measuring Method Based on a Single RGB Image
We should estimate the camera’s pose when utilizing a camera to measure volume. Traditional methods based on monocular camera lack depth, so they can’t estimate a camera’s pose from image to spatial features. ...
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Chapter and Conference Paper
Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs Using Confidence-Augmented Reinforcement Learning
Temporal knowledge graph completion (TKGC) aims to predict the missing links among the entities in a temporal knowledge graph (TKG). Most previous TKGC methods only consider predicting the missing links among ...
