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Found 8 papers, 0 papers with code
Balancing Security and Accuracy: A Novel Federated Learning Approach for Cyberattack Detection in Blockchain Networks
This paper presents a novel Collaborative Cyberattack Detection (CCD) system aimed at enhancing the security of blockchain-based data-sharing networks by addressing the complex challenges associated with noise addition in federated learning models.
Optimal Pricing of Internet of Things: A Machine Learning Approach
For service bundles, the subscription fee and data sizes of the grouped IoT services are optimized to maximize the total profit of cooperative service providers.
RF-based 3D skeletons
It maintains this accuracy even in the presence of multiple people, and in new environments that it has not seen in the training set.
Through-Wall Human Pose Estimation Using Radio Signals
Yet, unlike vision-based pose estimation, the radio-based system can estimate 2D poses through walls despite never trained on such scenarios.
Mobile Big Data Analytics Using Deep Learning and Apache Spark
The proliferation of mobile devices, such as smartphones and Internet of Things (IoT) gadgets, results in the recent mobile big data (MBD) era.
Deep Activity Recognition Models with Triaxial Accelerometers
Despite the widespread installation of accelerometers in almost all mobile phones and wearable devices, activity recognition using accelerometers is still immature due to the poor recognition accuracy of existing recognition methods and the scarcity of labeled training data.
Toward a Robust Sparse Data Representation for Wireless Sensor Networks
Our contributions that address three major issues include: 1) an effective method that extracts population sparsity of the data, 2) a sparsity ratio guarantee scheme, and 3) a customized learning algorithm of the sparsifying dictionary.
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs).
