Broadly speaking, building energy use prediction can be classified into two categories
based on modeling approaches namely engineering and Artificial Intelligence (AI). While …

Over the last two decades, multiple classifier system (MCS) or classifier ensemble has
shown great potential to improve the accuracy and reliability of remote sensing image …

Diversity among the base classifiers is deemed to be important when constructing a
classifier ensemble. Numerous algorithms have been proposed to construct a good …

Street traffic sign infrastructure remains an extremely difficult asset for local government to
manage due to its diverse physical structure and geographical distribution. A spatial …

We derive upper and lower limits on the majority vote accuracy with respect to individual
accuracy p, the number of classifiers in the pool (L), and the pairwise dependence between …

Medical image classification is an important task in computer-aided diagnosis systems. Its
performance is critically determined by the descriptiveness and discriminative power of …

This study looks at the relationships between different methods of classifier combination and
different measures of diversity. We considered 10 combination methods and 10 measures of …

Image classification is a complex process affected by some uncertainties and decisions
made by the researchers. The accuracy achieved by a supervised classification is largely …

Increasing amounts of data, together with more computing power and better machine
learning algorithms to analyse the data, are causing changes in almost every aspect of our …

Flood risk management generally relies on economic assessments performed by using flood
loss models of different complexity, ranging from simple univariable models to more complex …