Segmentation has been a rooted area of research having diverse dimensions. The roots of
image segmentation and its associated techniques have supported computer vision, pattern …

With the advent and advancement of machine learning and deep learning techniques,
machine-based recognition systems for mathematical text have captivated the attention of …

Mathematical entity recognition is indispensable for machines to accurately explain and
depict mathematical content and to enable adequate mathematical operations and …

Data centers are producing a lot of data as cloud-based smart grids replace traditional grids.
The number of automated systems has increased rapidly, which in turn necessitates the rise …

Contour Detection owes its own significance in performing semantic segmentation and
object classification. It is possible to recognize the edges of objects and readily locate them …

Machine learning-based translation models have recently hit the trend line and impacted the
pace of research in Natural Language Processing. The emerging trend of the era witnesses' …

Spondylolisthesis is a chronic disease, and a timely diagnosis of it may help in avoiding
surgery. Disease identification in x-ray radiographs is very challenging. Strengthening the …

In this paper, a new paradigm for network security is developed via the use of ensemble
learning. The primary objective of this study is to identify and stop the involvement of …

In an effort to advance personalized farming, this study presents a novel hybrid model that
combines Support Vector Machine (SVM) and Convolutional Neural Network (CNN) …

Digital Twin (DT) is a system of systems in which the conversion of every component,
dynamic, and firmware of a physical system into its digital equivalent takes place …