Anomaly detection in NetFlow network traffic using supervised machine learning algorithms
Anomaly detection is an important method for monitoring network traffic where is important to
successfully distinguish normal traffic from abnormal traffic. For this purpose, one could use …
successfully distinguish normal traffic from abnormal traffic. For this purpose, one could use …
DeepCar 5.0: vehicle make and model recognition under challenging conditions
A Amirkhani, AH Barshooi - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
Inspired by multi-agent systems (MASs) and ensemble models, a novel method of vehicle
make and model recognition (VMMR) based on a vehicle's front-view images is presented in …
make and model recognition (VMMR) based on a vehicle's front-view images is presented in …
Robust appearance modeling for object detection and tracking: a survey of deep learning approaches
A Mumuni, F Mumuni - Progress in Artificial Intelligence, 2022 - Springer
The task of object detection and tracking is one of the most complex and challenging
problems in artificial intelligence (AI) systems that model perception. Object tracking has …
problems in artificial intelligence (AI) systems that model perception. Object tracking has …
Intelligent fault diagnosis of rolling bearings based on the visibility algorithm and graph neural networks
S Ning, Y Ren, Y Wu - Journal of the Brazilian Society of Mechanical …, 2023 - Springer
Rolling bearing fault diagnosis methods based on deep learning models usually apply
regular data based on Euclidean space, and the relationship between data has not received …
regular data based on Euclidean space, and the relationship between data has not received …
Feature generation and multi-sequence fusion based deep convolutional network for breast tumor diagnosis with missing MR sequences
T Wang, H Wang, J Deng, D Zhang, J Feng… - … signal processing and …, 2023 - Elsevier
In breast tumor diagnostic tasks, joint analysis of multiple sequences of MRI can improve the
accuracy of diagnosis. More and more studies focus on the correlation between sequences …
accuracy of diagnosis. More and more studies focus on the correlation between sequences …
IoT-based classification and differential diagnosis of COVID-19 from CT Images using DexiNed filter, image blending and weighted ensemble CNNs
AH Barshooi - 2023 9th International Conference on Web …, 2023 - ieeexplore.ieee.org
The coronavirus, discovered for the first time in December 2019 in Wuhan, China, quickly
spread to more than two hundred countries and became a public health emergency. After …
spread to more than two hundred countries and became a public health emergency. After …
Music Genre Classification Using DenseNet and Data Augmentation.
It can be said that the automatic classification of musical genres plays a very important role
in the current digital technology world in which the creation, distribution, and enjoyment of …
in the current digital technology world in which the creation, distribution, and enjoyment of …
Ford Motor Company E-Commerce Development on Social Networks based on HED Feature Extraction, Machine Learning and Alan Mulally's Strategy
AH Barshooi - 2023 9th International Conference on Web …, 2023 - ieeexplore.ieee.org
In this article, a multi-stage E-commerce platform based on deep learning methods is
presented to improve Ford Motor Company's consumer engagement on the Instagram social …
presented to improve Ford Motor Company's consumer engagement on the Instagram social …
IDDM: An incremental dual-network detection model for in-situ inspection of large-scale complex product
F Zhang, Z Chen - Journal of Industrial Information Integration, 2023 - Elsevier
Appearance inspection is crucial for quality control during the manufacturing of large
complex products. In-situ visual inspection based on image processing and machine …
complex products. In-situ visual inspection based on image processing and machine …
Improving robustness of convolutional neural networks using element-wise activation scaling
Recent works reveal that re-calibrating intermediate activation of adversarial examples can
improve the adversarial robustness of CNN models. The state of the arts exploit this feature …
improve the adversarial robustness of CNN models. The state of the arts exploit this feature …