Clustering algorithms have successfully been applied as a digital image segmentation
technique in various fields and applications. However, those clustering algorithms are only …

In this paper, we propose a color-based segmentation method that uses the K-means
clustering technique to track tumor objects in magnetic resonance (MR) brain images. The …

In recent years, the electronic devices and wireless network are seen everywhere,
generating a massive amount of online surveillance video data that can be applied to …

In X-ray computed tomography imaging, the approaches used to determine the porosity of
the rock from a single computed tomography scan are based on image segmentation …

Breast cancer is one of the most common death causes amongst women all over the world.
Early detection of breast cancer plays a critical role in increasing the survival rate. Various …

This paper develops a non-model based vehicle tracking methodology for extracting road
user trajectories as they pass through the field of view of a 3D LiDAR sensor mounted on the …

This paper presents a review of the current literature on rough-set-and near-set-based
approaches to solving various problems in medical imaging such as medical image …

The application of specialized machine learning (ML) in petroleum engineering and
geoscience is increasingly gaining attention in the development of rapid and efficient …

Several high spatial resolution thermal infrared (TIR) missions are planned for the coming
decade and their data will be crucial to constrain volcanic activity patterns throughout pre …

The object of this study was to demonstrate the ability of machine learning (ML) methods for
the segmentation and classification of diabetic retinopathy (DR). Two-dimensional (2D) …