Results 161 to 170 of about 234,412 (208)

An Integrated Testbed for MITRE-Mapped Attack Emulation in Industrial Control Networks. [PDF]

Sensors (Basel)
Rahmani J, Detken KO, Sikora A.
europepmc   +1 more source

A hybrid KF-GAIN framework for dynamic state estimation in islanded microgrids under missing PMU data and line impedance uncertainty. [PDF]

Sci Rep
Masoudi MR, Mohammadi M, Zaker B, Keihan Asl D, Mostafanezhad M.   +4 more
europepmc   +1 more source

Early identification of abnormal pulmonary infectious diseases using unsupervised anomaly detection. [PDF]

Quant Imaging Med Surg
Liu R, Zhu Y, Lyu Z, Gao Y, Zhan Y, Zhan Y.   +5 more
europepmc   +1 more source

PCA-AE: Principal Component Analysis Autoencoder for Organising the Latent Space of Generative Networks

Journal of Mathematical Imaging and Vision, 2022
International audienceAutoencoders and generative models produce some of the most spectacular deep learning results to date. However, understanding and controlling the latent space of these models presents a considerable challenge.
Chi-Hieu Pham, Saïd Ladjal, Alasdair Newson   +2 more
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AE-MCCF: An Autoencoder-Based Multi-criteria Recommendation Algorithm

Arabian Journal for Science and Engineering, 2019
Recommender systems enable users to deal with the information overload problem by serving personalized predictions. Traditional recommendation techniques produce referrals for users by considering their overall opinions over items. On the other hand, users may consider several criteria while evaluating an item.
Zeynep Batmaz, Cihan Kaleli
openaire   +1 more source

AE-DCNN: Autoencoder Enhanced Deep Convolutional Neural Network For Malware Classification

2021 International Conference on Intelligent Technologies (CONIT), 2021
Malware classification is a problem of great significance in the domain of information security. This is because the classification of malware into respective families helps in determining their intent, activity, and level of threat. In this paper, we propose a novel deep learning approach to malware classification. The proposed method converts malware
Shashank Kumar, Shivangi Meena, Savya Khosla, Anil Singh Parihar   +3 more
openaire   +1 more source

PM-AE: Pyramid Memory Autoencoder for Unsupervised Textured Surface Defect Detection

2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), 2020
Anomaly detection for textured surface is a key task in product quality control. In recent years, supervised deep learning approaches have begun to be applied in this field, whereas most of the approaches are usually impracticable in collecting a large scale of defect samples. To this end, this paper proposes an efficient pyramid memory autoencoder.
Haiming Yao, Dan Li, Yiwen Zhu, Wenyong Yu   +3 more
openaire   +1 more source

SF-AE: Split Federated Autoencoder for Unsupervised IoT Intrusion Detection

Smart systems have become increasingly popular in recent years, widening the attack surface of cyber threats. Machine learning algorithms have been successfully integrated into modern security mechanisms to detect such attacks. Internet of Things (IoT) systems often have limited computational resources and are unable to execute entire machine learning ...
Augello, Andrea, De Paola, Alessandra, Giosue, Domenico, Lo Re, Giuseppe   +3 more
openaire   +1 more source

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Applied Soft Computing
Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data.
Chengjia Han, Zixin Wang, Yuguang Fu, Shirley Dyke, Adnan Shahriar   +4 more
openaire   +2 more sources