4.8 Article

Deep Anomaly Detection for Time-Series Data in Industrial IoT: A Communication-Efficient On-Device Federated Learning Approach

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Deep Fuzzy Hashing Network for Efficient Image Retrieval

Huimin Lu et al.

Summary: Our proposed deep fuzzy hashing network (DFHN) combines fuzzy logic technique and DNN to learn effective binary codes that leverage fuzzy rules to model data uncertainties. The generalized hamming distance derived from fuzzy logic theory is utilized in the convolutional and fully connected layers to model outputs, resulting in competitive retrieval accuracy and efficient training speed on large-scale image datasets: CIFAR-10 and NUS-WIDE, compared to state-of-the-art deep hashing approaches.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2021)

Article Computer Science, Theory & Methods

A multi-stage anomaly detection scheme for augmenting the security in IoT-enabled applications

Sahil Garg et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2020)

Article Computer Science, Theory & Methods

En-ABC: An ensemble artificial bee colony based anomaly detection scheme for cloud environment

Sahil Garg et al.

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING (2020)

Article Computer Science, Information Systems

Deep hierarchical encoding model for sentence semantic matching

Wenpeng Lu et al.

JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION (2020)

Article Computer Science, Information Systems

Dominant Data Set Selection Algorithms for Electricity Consumption Time-Series Data Analysis Based on Affine Transformation

Yi Wu et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Computer Science, Information Systems

Privacy-Preserving Traffic Flow Prediction: A Federated Learning Approach

Yi Liu et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Engineering, Multidisciplinary

Deep Reinforcement Learning Based Resource Management for Multi-Access Edge Computing in Vehicular Networks

Haixia Peng et al.

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING (2020)

Article Computer Science, Information Systems

A Hybrid Deep Learning-Based Model for Anomaly Detection in Cloud Datacenter Networks

Sahil Garg et al.

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT (2019)

Article Computer Science, Artificial Intelligence

Network anomaly detection using channel boosted and residual learning based deep convolutional neural network

Naveed Chouhan et al.

APPLIED SOFT COMPUTING (2019)

Article Computer Science, Information Systems

DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series

Mohsin Munir et al.

IEEE ACCESS (2019)

Article Computer Science, Artificial Intelligence

Web traffic anomaly detection using C-LSTM neural networks

Tae-Young Kim et al.

EXPERT SYSTEMS WITH APPLICATIONS (2018)

Article Engineering, Electrical & Electronic

Toward Energy-Efficient and Robust Large-Scale WSNs: A Scale-Free Network Approach

Haixia Peng et al.

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2016)

Article Computer Science, Artificial Intelligence

High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning

Sarah M. Erfani et al.

PATTERN RECOGNITION (2016)

Article Computer Science, Hardware & Architecture

Anomaly-based intrusion detection: privacy concerns and other problems

E Lundin et al.

COMPUTER NETWORKS (2000)