As the principal means of oil and natural gas transportation, oil and gas pipeline systems
suffer from common corrosion problems, accurate corrosion prediction of oil and gas …

The massive growth of data produced in the automotive industry by acquiring data during
production and test of vehicles requires effective and intelligent ways of analysing these …

In machine learning, the presumably best model is selected from a variety of model
candidates generated by testing different model types, hyperparameters, or feature subsets …

Early detection of Tuberculosis or TB can help in mitigating the chances of affecting the other
body parts like the kidney, spine and brain, thereby reducing the death rate due to this …

Bagging is one of the well-known ensemble learning methods, which combines several
classifiers trained on different subsamples of the dataset. However, a drawback of bagging …

The diagnosis of Parkinson's disease (PD) is important in neurological pathology for
appropriate medical therapy. Algorithms based on decision tree induction (DTI) have been …

Advancement and emergence of newer technologies such as analytics, artificial intelligence,
machine learning have impacted many sectors such as health care, automotive etc. In the …

The identification of landscape classes facilitates the implementation of planning strategies.
Although landscape patterns are key distinctive features of landscape classes, existing …

Cheese-making traits in dairy cattle are important to the dairy industry but are difficult to
measure at the individual level because there are limitations on collecting phenotypic …

Change detection (CD) is an active research topic in remote sensing applications including
urban studies, disaster assessment, and deforestation monitoring. In this paper, we propose …