[HTML][HTML] Adaptive UNet-based lung segmentation and ensemble learning with CNN-based deep features for automated COVID-19 diagnosis
A Das - Multimedia Tools and Applications, 2022 - Springer
COVID-19 disease is a major health calamity in twentieth century, in which the infection is
spreading at the global level. Developing countries like Bangladesh, India, and others are …
spreading at the global level. Developing countries like Bangladesh, India, and others are …
[HTML][HTML] Classification of diseases using machine learning algorithms: A comparative study
MA Moreno-Ibarra, Y Villuendas-Rey, MD Lytras… - Mathematics, 2021 - mdpi.com
Machine learning in the medical area has become a very important requirement. The
healthcare professional needs useful tools to diagnose medical illnesses. Classifiers are …
healthcare professional needs useful tools to diagnose medical illnesses. Classifiers are …
Semi-supervised segmentation of salt bodies in seismic images using an ensemble of convolutional neural networks
Y Babakhin, A Sanakoyeu, H Kitamura - Pattern Recognition: 41st DAGM …, 2019 - Springer
Seismic image analysis plays a crucial role in a wide range of industrial applications and
has been receiving significant attention. One of the essential challenges of seismic imaging …
has been receiving significant attention. One of the essential challenges of seismic imaging …
[HTML][HTML] Gender recognition by voice using an improved self-labeled algorithm
Speech recognition has various applications including human to machine interaction,
sorting of telephone calls by gender categorization, video categorization with tagging and so …
sorting of telephone calls by gender categorization, video categorization with tagging and so …
[HTML][HTML] A weighted voting ensemble self-labeled algorithm for the detection of lung abnormalities from X-rays
During the last decades, intensive efforts have been devoted to the extraction of useful
knowledge from large volumes of medical data employing advanced machine learning and …
knowledge from large volumes of medical data employing advanced machine learning and …
[HTML][HTML] Deep ensemble approach for pathogen classification in large-scale images using patch-based training and hyper-parameter optimization
Pathogenic bacteria present a major threat to human health, causing various infections and
illnesses, and in some cases, even death. The accurate identification of these bacteria is …
illnesses, and in some cases, even death. The accurate identification of these bacteria is …
[HTML][HTML] Heart disease prediction using concatenated hybrid ensemble classifiers
Heart disease is a leading global cause of mortality, demanding early detection for effective
and timely medical intervention. In this study, we propose a machine learning-based model …
and timely medical intervention. In this study, we propose a machine learning-based model …
Intelligent fault identification strategy of photovoltaic array based on ensemble self-training learning
Identifying Photovoltaic (PV) array faults is crucial for improving the service life and
consolidating system performance overall. The strategies based on the supervised Machine …
consolidating system performance overall. The strategies based on the supervised Machine …
Classification of lung diseases using deep learning models
M Zak, A Krzyżak - International Conference on Computational Science, 2020 - Springer
In this paper we address the problem of medical data scarcity by considering the task of
detection of pulmonary diseases from chest X-Ray images using small volume datasets with …
detection of pulmonary diseases from chest X-Ray images using small volume datasets with …
[HTML][HTML] A hybrid ensemble stacking model for gender voice recognition approach
Gender recognition by voice is a vital research subject in speech processing and acoustics,
as human voices have many remarkable characteristics. Voice recognition is beneficial in a …
as human voices have many remarkable characteristics. Voice recognition is beneficial in a …