[HTML][HTML] Classification of optimal brain tissue using dynamic region growing and fuzzy min-max neural network in brain magnetic resonance images
SL Bangare - Neuroscience Informatics, 2022 - Elsevier
On an MRI scan of the brain, the boundary between endocrine tissues is highly convoluted
and irregular. Outdated segmentation algorithms face a severe test. Machine learning as a …
and irregular. Outdated segmentation algorithms face a severe test. Machine learning as a …
Efficient framework for brain tumour classification using hierarchical deep learning neural network classifier
In this manuscript, an efficient framework is proposed for brain tumour classification (BTC)
based on hierarchical deep-learning neural network (HieDNN) classifier. Here, the input …
based on hierarchical deep-learning neural network (HieDNN) classifier. Here, the input …
A Novel Deep Learning‐Based Black Fungus Disease Identification Using Modified Hybrid Learning Methodology
S Karthikeyan, G Ramkumar… - Contrast Media & …, 2022 - Wiley Online Library
Currently, countries across the world are suffering from a prominent viral infection called
COVID‐19. Most countries are still facing several issues due to this disease, which has …
COVID‐19. Most countries are still facing several issues due to this disease, which has …
Identification of Heart Diseases using Novel Machine Learning Method
R Veeranjaneyulu, S Boopathi… - … on Advances in …, 2023 - ieeexplore.ieee.org
This study aims to enhance feature variety and organizationprocesses for heart disease
prediction using three different approaches. The integration of machine learning perception …
prediction using three different approaches. The integration of machine learning perception …
An unconventional approach for analyzing the mechanical properties of natural fiber composite using convolutional neural network
Over the past few years, natural fiber composites have been a strategy of rapid growth. The
computational methods have become a significant tool for many researchers to design and …
computational methods have become a significant tool for many researchers to design and …
Breast cancer classification using FCN and beta wavelet autoencoder
HN AlEisa, W Touiti, A Ali ALHussan… - Computational …, 2022 - Wiley Online Library
In this paper, a new classification approach of breast cancer based on Fully Convolutional
Networks (FCNs) and Beta Wavelet Autoencoder (BWAE) is presented. FCN, as a powerful …
Networks (FCNs) and Beta Wavelet Autoencoder (BWAE) is presented. FCN, as a powerful …
Brain Tumor Detection using Decision‐Based Fusion Empowered with Fuzzy Logic
Brain tumor is regarded as one of the fatal and dangerous diseases on the planet. It is
present in the form of uncontrolled and irregular cells in the brain of an infected individual …
present in the form of uncontrolled and irregular cells in the brain of an infected individual …
Deep neuro-fuzzy logic technique for brain meningiomasa prediction
Simulation approaches based on Deep Learning (DL) techniques have several
computational stages that present information at various levels of complexity. DL has …
computational stages that present information at various levels of complexity. DL has …
Simulation process of injection molding and optimization for automobile instrument parameter in embedded system
The automobile instrument is the indispensable item that is essential to keep the driver
conversant of the process of the engineer and the other system. There are different …
conversant of the process of the engineer and the other system. There are different …
Multi-Feature Classification of Breast Cancer Histopathology Images: An Experimental Investigation in Machine Learning and Deep Learning Paradigm
The existing practice for Breast Cancer (BC) characterization includes histopathological
analysis, which is tedious and time-consuming due to massive data analysis. Further, such …
analysis, which is tedious and time-consuming due to massive data analysis. Further, such …