Purpose Although classical techniques for image segmentation may work well for some
images, they may perform poorly or not work at all for others. It often depends on the …

In brain magnetic resonance (MR) image segmentation, the current Otsu method is often
difficult to take both accuracy and anti-noise capability into consideration. So, in this paper …

Pancreatic cancer is the fourth leading cause of cancer-related death worldwide. Pancreatic
tumours are characterised by a peculiar cell progression in intestinal enzymes and hormone …

As a popular optimization, particle swarm optimization has attracted many researcher's
attention and also been successfully applied to solve many real world problems. As …

Cardiovascular disease (CVD) remains the primary reason for illness and death throughout
the world despite tremendous progress in diagnosis and treatment. Artificial intelligence (AI) …

In cases where the success of artificial intelligence (AI) approaches is more focused on the
multi-agent system (MAS) than those that may make AI understandable to humans, in light of …

In order to deeply study the macroenvironment, current situation, and the core elements
affecting the operation of the product brand system, this paper further improves the product …

In this paper, oppositional based Seagull optimization Algorithm Based 3D Deep
Convolution Neural Network (OSOA-3DCNN) is developed to semantic segmentation of the …

This paper proposes to enhance the Artificial Bee Colony (ABC) metaheuristic with a Tabu
adaptive memory to optimize the multilevel thresholding for Image Segmentation. This novel …

The process of image segmentation involves dividing a digital image into multiple parts to
simplify or change its representation into something more meaningful and easier to analyze …