Abstract Applications of Artificial Intelligence (AI), Deep Learning (DL), and Machine
Learning (ML) are becoming common in the field of civil and infrastructure engineering. This …

There has been a significant increase in the availability of global high-resolution land cover
(HRLC) datasets due to growing demand and favorable technological advancements …

Purpose: This work proposes the hypothesis that data oversampling may lead to dataset
simplification according to selected data difficulty metrics and that such simplification …

Textile reinforced mortar composites (TRMs) experience various types of damage. In this
study, these damage mechanisms (such as cracking and non-cracking) were understood or …

Filter methods are a class of feature selection techniques used to identify a subset of
informative features during data preprocessing. While the differential efficacy of these …

In the bio-molecular field, epitope classification is essential in vaccine development. A
machine learning-based approach has been used for epitope classification using peptide …

Refactoring enhances software quality without altering its functional behaviors.
Understanding the refactoring activities of developers is crucial to improving software …

Background: Data quality is vital in software analytics, particularly for machine learning (ML)
applications like software defect prediction (SDP). Despite the widespread use of ML in …

Machine learning algorithms are frequently used for classification problems on tabular
datasets. In order to make informed decisions about model selection and design, it is crucial …

Context: Soft biometrics is a field that aids traditional biometrics through attribute
identification using descriptors such as hair type, ethnicity, or gender. When employed to …