A comprehensive review of bat inspired algorithm: variants, applications, and hybridization

M Shehab, MA Abu-Hashem, MKY Shambour… - … Methods in Engineering, 2023 - Springer
Bat algorithm (BA) is one of the promising metaheuristic algorithms. It proved its efficiency in
dealing with various optimization problems in diverse fields, such as power and energy …

Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network

SH Wang, VV Govindaraj, JM Górriz, X Zhang… - Information …, 2021 - Elsevier
Abstract (Aim) COVID-19 is an infectious disease spreading to the world this year. In this
study, we plan to develop an artificial intelligence based tool to diagnose on chest CT …

A systematic review on bat algorithm: Theoretical foundation, variants, and applications

T Agarwal, V Kumar - Archives of Computational Methods in Engineering, 2022 - Springer
Bat algorithm (BA) is a population-based metaheuristic algorithm inspired by echolocation
behavior of bat. After the development of BA in 2010, it becomes the attention of researchers …

COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis

SH Wang, DR Nayak, DS Guttery, X Zhang, YD Zhang - Information Fusion, 2021 - Elsevier
Aim: COVID-19 is a disease caused by a new strain of coronavirus. Up to 18th October
2020, worldwide there have been 39.6 million confirmed cases resulting in more than 1.1 …

Pathological brain detection based on AlexNet and transfer learning

S Lu, Z Lu, YD Zhang - Journal of computational science, 2019 - Elsevier
The aim of this study is to automatically detect pathological brain in magnetic resonance
images (MRI) based on deep learning structure and transfer learning. Deep learning is now …

Pre-trained deep learning models for brain MRI image classification

S Krishnapriya, Y Karuna - Frontiers in Human Neuroscience, 2023 - frontiersin.org
Brain tumors are serious conditions caused by uncontrolled and abnormal cell division.
Tumors can have devastating implications if not accurately and promptly detected. Magnetic …

Deep convolutional neural networks with transfer learning for automated brain image classification

T Kaur, TK Gandhi - Machine vision and applications, 2020 - Springer
MR brain image categorization has been an active research domain from the last decade.
Several techniques have been devised in the past for MR image categorization, starting from …

Automated brain image classification based on VGG-16 and transfer learning

T Kaur, TK Gandhi - 2019 international conference on …, 2019 - ieeexplore.ieee.org
The last few decades have witnessed active research in the domain of pathological brain
image classification starting from classical to the deep learning approaches like …

AVNC: attention-based VGG-style network for COVID-19 diagnosis by CBAM

SH Wang, SL Fernandes, Z Zhu… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
(Aim) To detect COVID-19 patients more accurately and more precisely, we proposed a
novel artificial intelligence model.(Methods) We used previously proposed chest CT dataset …

A five-layer deep convolutional neural network with stochastic pooling for chest CT-based COVID-19 diagnosis

YD Zhang, SC Satapathy, S Liu, GR Li - Machine vision and applications, 2021 - Springer
Abstract Till August 17, 2020, COVID-19 has caused 21.59 million confirmed cases in more
than 227 countries and territories, and 26 naval ships. Chest CT is an effective way to detect …