Automated detection of brain tumor through magnetic resonance images using convolutional neural network

S Gull, S Akbar, HU Khan - BioMed Research International, 2021 - Wiley Online Library
Brain tumor is a fatal disease, caused by the growth of abnormal cells in the brain tissues.
Therefore, early and accurate detection of this disease can save patient's life. This paper …

Prediction model of dementia risk based on XGBoost using derived variable extraction and hyper parameter optimization

SE Ryu, DH Shin, K Chung - IEEE Access, 2020 - ieeexplore.ieee.org
With the development of healthcare technologies, the elderly population has grown and
therefore populating ageing has emerged as a social issue. It is a cause of rise in patients …

A hybrid approach to segment and detect brain abnormalities from MRI scan

M Raja, S Vijayachitra - Expert Systems with Applications, 2023 - Elsevier
The Detection of brain abnormality is a complex task. The images captured from the MRI
scan machines have numerous information, and it is difficult to segment the appropriate …

Hyperparameter optimization of LSTM based Driver's aggressive behavior prediction model

DD Hema, KA Kumar - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
Traffic safety in the area of Intelligent Transportation System can be improved by predicting
driver behavior automatically. Aggressive driving is significant indicator for collision. Several …

Optimized deep neural network based intelligent decision support system for traffic state prediction

D Deva Hema, KA Kumar - International journal of intelligent …, 2023 - Springer
Importance of efficient short term traffic state prediction has been increased for accurate
traffic planning in the domain of an Intelligent Transportation System. Modeling variety of …

Segmentation Technology of Nucleus Image Based on U‐Net Network

J Fang, QB Zhou, S Wang - Scientific Programming, 2021 - Wiley Online Library
To solve the problems of rough edge and poor segmentation accuracy of traditional neural
networks in small nucleus image segmentation, a nucleus image segmentation technology …

A weighted bounded Hessian variational model for image labeling and segmentation

Y Yang, Q Zhong, Y Duan, T Zeng - Signal Processing, 2020 - Elsevier
Natural images are usually composed of multiple objects at different scales in flat and
slanted regions. Traditional labeling/segmentation approaches based on total variation …

Medical image segmentation algorithm based on positive scaling invariant-self encoding CCA

FP An, J Liu, J Wang - Biomedical Signal Processing and Control, 2021 - Elsevier
The quality of medical image segmentation results directly affect disease analysis and
diagnosis. Although traditional medical image segmentation methods have achieved certain …

Levenberg–marquardt–lstm based efficient rear-end crash risk prediction system optimization

DD Hema, KA Kumar - International Journal of Intelligent Transportation …, 2022 - Springer
The Almost 1.3 million casualties are reported round a calendar year due to road accidents.
Advanced collision avoidance systems play major role in predicting the collision risk to avoid …

Comparative analysis and experience of using social network analysis information systems

OB Kalugina, UV Mikhailova… - Journal of Computational …, 2019 - ingentaconnect.com
At present, in open sources of social networks and mass media every second there is a
huge amount of information, the analysis of which can significantly effect both the activities of …