Classification and segmentation of periodontal cyst for digital dental diagnosis using deep learning

TK Lakshmi, J Dheeba - Computer Assisted Methods in …, 2022 - cames.ippt.gov.pl
The digital revolution is changing every aspect of life by simulating the ways humans think,
learn and make decisions. Dentistry is one of the major fields where subsets of artificial …

[PDF][PDF] Latency Reduction in Medical IoT Using Fuzzy Systems by Enabling Optimized Fog Computing

S Aiswarya, A Geetha, K Ramesh… - … Journal of Electrical …, 2022 - researchgate.net
Fog computing technology is an emerging computing method that functions in a distributed
decentralized environment. Cloud computing features are being brought closer to edge …

An improvement of communication stability on underwater sensor network using balanced energy efficient joining distance matrix

VP Natarajan, K Thandapani - International Journal of System Assurance …, 2022 - Springer
Efficient deployment of underwater sensor networks (UWSN's) is the primary goal of
maximizing area coverage. The placement of the sensors also means that they are used to …

[PDF][PDF] Biologically inspired CNN network for brain tumor abnormalities detection and features extraction from MRI images

C Swarup, A Kumar, KU Singh, T Singh, L Raja… - Hum.-Cent. Comput. Inf …, 2022 - hcisj.com
Image segmentation has become increasingly important in medical image analysis, but it
does not remain easy to solve. Medical imaging is becoming more relevant since there is …

E-healthcare application cyber security analysis using quantum machine learning in malicious user detection

Z Liu, X Jia, B Li - Optical and Quantum Electronics, 2024 - Springer
In the medical field, it is crucial to manage visual and auditory data generated by Internet of
Things (IoT) devices. Cloud servers are often used to manage the massive amounts of data …

Fishier mantis optimiser: a swarm intelligence algorithm for clustering images of COVID-19 pandemic

J Rahebi - International Journal of Nanotechnology, 2023 - inderscienceonline.com
In this study, an automated segmentation method is used to increase the speed of diagnosis
and reduce the segmentation error of CT scans of the lung. In the proposed technique, the …

Detection of brain tumour using machine learning based framework by classifying MRI images

P Nancy, G Murugesan, AS Zamani… - International …, 2023 - inderscienceonline.com
The fatality rate has risen in recent years due to an increase in the number of encephaloma
tumours in each age group. Because of the complicated structure of tumours and the …

Feature recognition of state signal of electromechanical integration railway turnout over health parameters using CMOS area array technology

Y Zhou, A Sharma, M Shabaz - The Journal of Engineering, 2022 - Wiley Online Library
Railway turnout is the most important line connection equipment of high‐speed railway
system. In order to improve the monitoring and maintenance of high‐speed railway turnout …

Applications of machine learning and internet of things in agriculture

AN Abougreen, C Chakraborty - Green Technological Innovation for …, 2021 - Springer
With the rapid advancement of technology, people are passionate to get more intelligent
living. Since agriculture is one of the significant industries that need to be developed in order …

SDAFA: Secure Data Aggregation in Fog-Assisted Smart Grid Environment

Shruti, S Rani, A Singh, R Alkanhel, DSM Hassan - Sustainability, 2023 - mdpi.com
The tremendous growth of about 8 billion devices connected to each other in various
domains of Internet of Things (IoT)-based applications have attracted researchers from both …