Explainable intrusion detection systems (x-ids): A survey of current methods, challenges, and opportunities
The application of Artificial Intelligence (AI) and Machine Learning (ML) to cybersecurity
challenges has gained traction in industry and academia, partially as a result of widespread …
challenges has gained traction in industry and academia, partially as a result of widespread …
[HTML][HTML] A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …
belonging to one class is lower than the other. Ensemble learning combines multiple models …
[HTML][HTML] A survey on the interpretability of deep learning in medical diagnosis
Q Teng, Z Liu, Y Song, K Han, Y Lu - Multimedia Systems, 2022 - Springer
Deep learning has demonstrated remarkable performance in the medical domain, with
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
[HTML][HTML] A novel fraud detection and prevention method for healthcare claim processing using machine learning and blockchain technology
Healthcare fraud is a global problem affecting both developing and developed countries. It is
the deliberate attempt of the perpetrators to take undue advantage of the inefficiencies in …
the deliberate attempt of the perpetrators to take undue advantage of the inefficiencies in …
[HTML][HTML] Explainable AI and machine learning: performance evaluation and explainability of classifiers on educational data mining inspired career counseling
Abstract Machine Learning concept learns from experiences, inferences and conceives
complex queries. Machine learning techniques can be used to develop the educational …
complex queries. Machine learning techniques can be used to develop the educational …
Process modelling integrated with interpretable machine learning for predicting hydrogen and char yield during chemical looping gasification
Chemical looping gasification (CLG) is a promising thermochemical process for the
production of H 2. CLG process is mainly based on oxygen transfer from an air reactor to a …
production of H 2. CLG process is mainly based on oxygen transfer from an air reactor to a …
[HTML][HTML] How to bring UHI to the urban planning table? A data-driven modeling approach
MP Acosta, F Vahdatikhaki, J Santos… - Sustainable Cities and …, 2021 - Elsevier
While temperature rises in urbanized area there is a growing concern among key decision-
makers and urban planners to actively incorporate Urban Heat Island (UHI)-related …
makers and urban planners to actively incorporate Urban Heat Island (UHI)-related …
[HTML][HTML] Special issue on ensemble learning and applications
P Pintelas, IE Livieris - Algorithms, 2020 - mdpi.com
During the last decades, in the area of machine learning and data mining, the development
of ensemble methods has gained a significant attention from the scientific community …
of ensemble methods has gained a significant attention from the scientific community …
[HTML][HTML] A convolutional autoencoder topology for classification in high-dimensional noisy image datasets
Deep convolutional neural networks have shown remarkable performance in the image
classification domain. However, Deep Learning models are vulnerable to noise and …
classification domain. However, Deep Learning models are vulnerable to noise and …
A multi-view-CNN framework for deep representation learning in image classification
Deep representation learning in image classification is an area in computer vision where
deep Convolutional Neural Networks (CNNs) have flourished. Nevertheless, developing an …
deep Convolutional Neural Networks (CNNs) have flourished. Nevertheless, developing an …