Image segmentation is the process of splitting a digital image into distinct segments or
categories based on shared characteristics like texture, color, and intensity. Its primary aim is …

The rapid expansion of medical data poses numerous challenges for Machine Learning
(ML) tasks due to their potential to include excessive noisy, irrelevant, and redundant …

Liver-related diseases significantly contribute to global mortality rates. Accurate
segmentation of liver disease from CT scans is essential for early diagnosis and treatment …

Abstract Chest diseases, especially COVID-19, have quickly spread throughout the world
and caused many deaths. Finding a rapid and accurate diagnostic tool was indispensable to …

This study aims to develop a Sustainable Integrated Production-inventory (SIPI) model
considering carbon emissions, electricity consumption, and fuel consumption in a stochastic …

This paper introduces the mixed-strategy Harris hawk optimization (MSHHO) algorithm as
an enhancement to address the limitations of the conventional Harris hawk optimization …

Threshold based segmentation method is widely used because of its simplicity, high
efficiency and easy implementation. However, as the number of thresholds increases, the …

To recognize the potential for colon polyps to develop into cancer over time, early diagnosis
is crucial for preventative healthcare. Timely identification significantly improves the …

Abstract Vision Transformers (ViTs) have emerged as a promising approach for visual
recognition tasks, revolutionizing the field by leveraging the power of transformer-based …

Artificial neural network (ANN), developed by modeling the nervous system of the human
brain, is an important and effective data processing method used today. The most important …