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Survey of technology in network security situation awareness
J Zhang, H Feng, B Liu, D Zhao - Sensors, 2023 - mdpi.com
Network security situation awareness (NSSA) is an integral part of cybersecurity defense,
and it is essential for cybersecurity managers to respond to increasingly sophisticated cyber …
and it is essential for cybersecurity managers to respond to increasingly sophisticated cyber …
Particle swarm optimized federated learning for industrial IoT and smart city services
Most of the research on Federated Learning (FL) has focused on analyzing global
optimization, privacy, and communication, with limited attention focusing on analyzing the …
optimization, privacy, and communication, with limited attention focusing on analyzing the …
Intelligent fusion of deep features for improved waste classification
In this article, we address the problem of an image-based automatic classification of waste
materials. Given the large number of waste categories and the importance of proper …
materials. Given the large number of waste categories and the importance of proper …
Deep learning based multimodal urban air quality prediction and traffic analytics
Urban activities, particularly vehicle traffic, are contributing significantly to environmental
pollution with detrimental effects on public health. The ability to anticipate air quality in …
pollution with detrimental effects on public health. The ability to anticipate air quality in …
Attention-based modality-gated networks for image-text sentiment analysis
Sentiment analysis of social multimedia data has attracted extensive research interest and
has been applied to many tasks, such as election prediction and products evaluation …
has been applied to many tasks, such as election prediction and products evaluation …
Active balancing mechanism for imbalanced medical data in deep learning–based classification models
Imbalanced data always has a serious impact on a predictive model, and most under-
sampling techniques consume more time and suffer from loss of samples containing critical …
sampling techniques consume more time and suffer from loss of samples containing critical …
[HTML][HTML] Ensembles of deep learning models and transfer learning for ear recognition
The recognition performance of visual recognition systems is highly dependent on extracting
and representing the discriminative characteristics of image data. Convolutional neural …
and representing the discriminative characteristics of image data. Convolutional neural …
Pose estimation and detection for event recognition using Sense-Aware features and Adaboost classifier
I Akhter, A Jalal, K Kim - 2021 International Bhurban …, 2021 - ieeexplore.ieee.org
To examine events identification and recognition in sequential images, approaches used
several parameters such as size, location or position of the human body parts along with its …
several parameters such as size, location or position of the human body parts along with its …
Fault diagnosis of rotary machine bearings under inconsistent working conditions
M Sohaib, JM Kim - IEEE Transactions on Instrumentation and …, 2019 - ieeexplore.ieee.org
This article proposes a fault diagnosis (FD) method that is based on bispectrum analysis and
a convolutional neural network (CNN) to identify bearing faults under inconsistent working …
a convolutional neural network (CNN) to identify bearing faults under inconsistent working …
Automatic detection of passable roads after floods in remote sensed and social media data
This paper addresses the problem of floods classification and floods aftermath detection
based on both social media and satellite imagery. Automatic detection of disasters such as …
based on both social media and satellite imagery. Automatic detection of disasters such as …