Optimal scheduling of demand side load management of smart grid considering energy efficiency

S Balouch, M Abrar, H Abdul Muqeet… - Frontiers in Energy …, 2022 - frontiersin.org
The purpose of this research is to provide power grid energy efficiency solutions. In this
paper, a comprehensive review and its optimal solution is proposed considering the various …

Accurate detection of brain tumor using optimized feature selection based on deep learning techniques

PK Ramtekkar, A Pandey, MK Pawar - Multimedia Tools and Applications, 2023 - Springer
An unusual increase of nerves inside the brain, which disturbs the actual working of the
brain, is called a brain tumor. It has led to the death of lots of lives. To save people from this …

Innovative brain tumor detection using optimized deep learning techniques

PK Ramtekkar, A Pandey, MK Pawar - International Journal of System …, 2023 - Springer
An unusual increase of nerves inside the brain, which disturbs the actual working of the
brain, is called a brain tumor. It has led to the death of lots of lives. To save people from this …

Multi-input Unet model based on the integrated block and the aggregation connection for MRI brain tumor segmentation

L Fang, X Wang - Biomedical Signal Processing and Control, 2023 - Elsevier
With the growth of data information and the development of computer equipment, it is
extremely time-consuming and laborious to rely on the traditional manual segmentation of …

WSSOA: whale social spider optimization algorithm for brain tumor classification using deep learning technique

AK Mandle, SP Sahu, GP Gupta - International Journal of Information …, 2024 - Springer
Brain tumors can have detrimental effects on brain function and pose a serious threat to life.
Detecting and treating brain tumors early is vital for saving lives. However, identifying tumor …

A two-step approach for classification in Alzheimer's disease

I De Falco, G De Pietro, G Sannino - Sensors, 2022 - mdpi.com
The classification of images is of high importance in medicine. In this sense, Deep learning
methodologies show excellent performance with regard to accuracy. The drawback of these …

Optimized Convolutional Neural Network for Deregulated Congestion Management

D Bosupally, V Muniyamuthu… - … Conference on Circuit …, 2023 - ieeexplore.ieee.org
Congestion in power systems primarily caused by deregulation of the power system and
rising electricity consumption. Grid congestion occurrences are possible due to increased …

A robust genetic algorithm-based optimal feature predictor model for brain tumour classification from MRI data

M Thayumanavan, A Ramasamy - Network: Computation in Neural …, 2024 - Taylor & Francis
Brain tumour can be cured if it is initially screened and given timely treatment to the patients.
This proposed idea suggests a transform-and windowing-based optimization strategy for …

Optimized brain tumor analysis in FLAIR-MRI LGG images: leveraging transfer learning and optimization for enhanced diagnosis and localization

PS Kumar, VP Sakthivel, M Raju… - International Journal of …, 2024 - search.proquest.com
This research endeavour conducts a comprehensive exploration of an efficient approach for
categorizing and delineating brain tumors in fluid-attenuated inversion recovery magnetic …

[PDF][PDF] EDGE ENHANCE SPARSE DEEP AUTO ENCODER MODEL FOR HIGH-ACCURACY BRAIN TUMOR DETECTION IN MRI IMAGES

S JAGA, KR DEVI - Journal of Theoretical and Applied Information …, 2024 - jatit.org
Brain tumors are among the most lethal cancerous diseases, with their severity making them
a leading cause of cancer-related deaths. The treatment of brain tumors depends on the …