An extensive review on emerging advancements in thermography and convolutional neural networks for breast cancer detection

J Iyadurai, M Chandrasekharan, S Muthusamy… - Wireless Personal …, 2024 - Springer
Breast cancer remains a significant health concern, necessitating early and accurate
detection methods to reduce mortality rates. This review examines the use of thermography …

Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review

MS Islam, F Al Farid, FMJM Shamrat, MN Islam… - PeerJ Computer …, 2024 - peerj.com
The global spread of SARS-CoV-2 has prompted a crucial need for accurate medical
diagnosis, particularly in the respiratory system. Current diagnostic methods heavily rely on …

Deep learning network selection and optimized information fusion for enhanced COVID‐19 detection

MU Ali, A Zafar, J Tanveer, MA Khan… - … Journal of Imaging …, 2024 - Wiley Online Library
This study proposes a wrapper‐based technique to improve the classification performance
of chest infection (including COVID‐19) detection using X‐rays. Deep features were …

[HTML][HTML] Enhanced COVID-19 detection from x-ray images with convolutional neural network and transfer learning

Q Bani Baker, M Hammad, M Al-Smadi, H Al-Jarrah… - Journal of …, 2024 - mdpi.com
The global spread of Coronavirus (COVID-19) has prompted imperative research into
scalable and effective detection methods to curb its outbreak. The early diagnosis of COVID …

A novel Adaptive Neural Network-Based Laplacian of Gaussian (AnLoG) classification algorithm for detecting diabetic retinopathy with colour retinal fundus images

MD Ramasamy, K Periasamy, S Periasamy… - Neural Computing and …, 2024 - Springer
Diabetic retinopathy (DR) is a human eye disease in which the eye's retina is damaged in
diabetics. Diabetic retinopathy can be diagnosed by manually interpreting retinal fundus …

A novel method for prediction and analysis of COVID 19 transmission using machine learning based time series models

S Mann, D Yadav, S Muthusamy, D Rathee… - Wireless Personal …, 2023 - Springer
Coronavirus has been avowed world epidemic by the Organisation Mondiale de la Santé on
March 11th 2020. Formerly, numerous investigators have endeavoured to envisage …

An efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models

K Mukilan, C Rameshbabu, B Baranitharan… - Neural Computing and …, 2024 - Springer
Abstract The Engineering Procurement Construction (EPC) contract systems are widely
employed in the construction industry. Among the prevalent issues in this sector, cash flow …

C-Hybrid-NET: A self-attention-based COVID-19 screening model based on concatenated hybrid 2D-3D CNN features from chest X-ray images

K Bayoudh, F Hamdaoui, A Mtibaa - Multimedia Tools and Applications, 2024 - Springer
The outbreak of novel coronavirus (2019-nCOV, commonly known as COVID-19) was
declared a global pandemic by the World Health Organization (WHO) in March 2020. An …

A New Method for Detecting the Fatigue Using Automated Deep Learning Techniques for Medical Imaging Applications

NS Gnanadesigan, GAA Lincoln, N Dhanasegar… - Wireless Personal …, 2024 - Springer
In the human race, Fatigue may contribute to a decline in efficiency. Fatigue is a risk factor
for health and a component of quality degradation. The effects of Fatigue include sleep …

A Novel Method for Illegal Driver Detection and Legal Driver Identification Using Multitask Learning Based LSTM Models for Real Time Applications

M Manoharan, K Muthukrishnan, G Balan… - Wireless Personal …, 2024 - Springer
Abstract The Industrial Internet of Things is becoming the novel driving force in the
automotive industry, assembly travel more suitable for individuals. Despite this, there are still …