M
Md. Milon Islam
Researcher at Khulna University of Engineering & Technology
Publications - 49
Citations - 3825
Md. Milon Islam is an academic researcher from Khulna University of Engineering & Technology. The author has contributed to research in topics: Deep learning & Population. The author has an hindex of 20, co-authored 49 publications receiving 1214 citations. Previous affiliations of Md. Milon Islam include Khulna University & University of Waterloo.
Papers
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Attack and anomaly detection in IoT sensors in IoT sites using machine learning approaches
TL;DR: Performances of several machine learning models have been compared to predict attacks and anomalies on the IoT systems accurately and other metrics prove that Random Forest performs comparatively better.
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A Combined Deep CNN-LSTM Network for the Detection of Novel Coronavirus (COVID-19) Using X-ray Images
TL;DR: This paper aims to introduce a deep learning technique based on the combination of a convolutional neural network (CNN) and long short-term memory (LSTM) to diagnose COVID-19 automatically from X-ray images, which achieved desired results on the currently available dataset.
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Development of Smart Healthcare Monitoring System in IoT Environment.
TL;DR: A smart healthcare system in IoT environment that can monitor a patient’s basic health signs as well as the room condition where the patients are now in real-time is proposed.
Posted ContentDOI
A Combined Deep CNN-LSTM Network for the Detection of Novel Coronavirus (COVID-19) Using X-ray Images
TL;DR: This paper aims to introduce a deep learning technique based on the combination of a convolutional neural network (CNN) and long short -term memory (LSTM) to diagnose COVID-19 automatically from X-ray images.
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Predictive Data Mining Models for Novel Coronavirus (COVID-19) Infected Patients’ Recovery
TL;DR: The results of the present study have shown that the model developed with decision tree data mining algorithm is more efficient to predict the possibility of recovery of the infected patients from COVID-19 pandemic with the overall accuracy of 99.85% which stands to be the best model developed among the models developed with other algorithms.