Hybrid optimization enabled trust-based secure routing with deep learning-based attack detection in VANET
Vehicular ad-hoc network (VANET) model is easy to arrange and inexpensive answer for
clever traffic control and traffic failure protective measures. Generally, the nodes present in …
clever traffic control and traffic failure protective measures. Generally, the nodes present in …
Deep learning in medicine: Advancing healthcare with intelligent solutions and the future of holography imaging in early diagnosis
Deep Learning (DL) is currently transforming health services by significantly improving early
cancer diagnosis, drug discovery, protein–protein interaction analysis, and gene editing …
cancer diagnosis, drug discovery, protein–protein interaction analysis, and gene editing …
An experimental approach towards the performance assessment of various optimizers on convolutional neural network
S Vani, TVM Rao - 2019 3rd international conference on trends …, 2019 - ieeexplore.ieee.org
Artificial Intelligence is a technique of modeling a computer, a computer administered-robot,
in the indistinguishable manner the acute humans reflect. Machine Learning is a mechanism …
in the indistinguishable manner the acute humans reflect. Machine Learning is a mechanism …
[HTML][HTML] Development and integration of VGG and dense transfer-learning systems supported with diverse lung images for discovery of the Coronavirus identity
WA Hamwi, MM Almustafa - Informatics in Medicine Unlocked, 2022 - Elsevier
The contagious SARS-CoV-2 has had a tremendous impact on the life and health of many
communities. It was first rampant in early 2019 and so far, 539 million cases of COVID-19 …
communities. It was first rampant in early 2019 and so far, 539 million cases of COVID-19 …
Comparison of various learning rate scheduling techniques on convolutional neural network
J Konar, P Khandelwal… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
The learning rate is a hyperparameter which determines how much the model should
change concerning the error each time the model parameters are updated. It is important to …
change concerning the error each time the model parameters are updated. It is important to …
Real time road traffic event detection using Twitter and spark
KR Pandhare, MA Shah - 2017 International conference on …, 2017 - ieeexplore.ieee.org
Because of its real-time nature Twitter is a powerful source of information for detecting real
time event happening in the surrounding. People make tweets on whatever events they are …
time event happening in the surrounding. People make tweets on whatever events they are …
Detection of COVID-19 Infection in CT and X-ray images using transfer learning approach
A Tiwari, S Tripathi, DC Pandey… - … and Health Care, 2022 - content.iospress.com
BACKGROUND: The infection caused by the SARS-CoV-2 (COVID-19) pandemic is a threat
to human lives. An early and accurate diagnosis is necessary for treatment. OBJECTIVE …
to human lives. An early and accurate diagnosis is necessary for treatment. OBJECTIVE …
Using a method based on a modified K-means clustering and mean shift segmentation to reduce file sizes and detect brain tumors from magnetic resonance (MRI) …
JH Kim, S Lee, GS Lee, YS Park, YP Hong - Wireless Personal …, 2016 - Springer
In this paper, we propose a method of elaborating and detecting brain tumor from MRI
suitable for information sharing via the internet for a healthcare provider. This method allows …
suitable for information sharing via the internet for a healthcare provider. This method allows …
Feature selection on high dimensional data using wrapper based subset selection
In recent years, feature subset selection and classification in high dimensional data is a
major challenge faced by the researchers. The main aim of the feature subset selection is to …
major challenge faced by the researchers. The main aim of the feature subset selection is to …
Data augmentation for heart arrhythmia classification
In this paper, we introduce a technique for data augmentation that has been applied to an
ECG dataset from the UKBiobank for heart arrhythmia classification using the XGBoost …
ECG dataset from the UKBiobank for heart arrhythmia classification using the XGBoost …