image segmentation

Ensemble Methods Based on Centering for Image Segmentation

Ensemble methods can be used for many tasks, some of the most popular being: classification, regression, and image segmentation. Image segmentation is a challenging task, where the use of ensemble machine learning methods provides an opportunity to improve the accuracy of neural network predictions.

OPTIMIZATION OF OBJECT DETECTION IN CLOSED SPACE USING MOBILE ROBOTIC SYSTEMS WITH OBSTACLE AVOIDANCE

Introducing neural network training process modification that uses combination of several datasets to optimize search of objects and obstacles using mobile robotic systems in a closed space. The study includes an analysis of papers and existing approaches aiming to solve the problem of object boundary detection and discovers the key features of several neural network architectures. During research, it was discovered that there is an insufficient amount of data about the effectiveness of using obstacle detection approaches by mobile robotics systems in a closed space.

Mobile Information System for Human Nutrition Control

It is acknowledged that each person's life, group of people and nation is formed depending on geographical, economic, political, cultural and religious conditions. Lifestyle is formed as a result of daily repetition and consists of the following factors: nutrition, exercise, the presence of bad habits, moral and spiritual development, and so on. In recent decades, lifestyle has been considered an integral part of well-being, leading to increased research. According to the scientist's study, more than half of health problems are related to diet.

Software Implementation of Gesture Recognition Algorithm Using Computer Vision

This paper examines the main methods and principles of image formation, display of the sign language recognition algorithm using computer vision to improve communication between people with hearing and speech impairments. This algorithm allows to effectively recognize gestures and display information in the form of labels. A system that includes the main modules for implementing this algorithm has been designed.

Застосування методів штучного інтелекту до сегментації графічного образу

An efficient graph-based image segmentation algorithm (EGBIS) is considered. The aspects of an efficient algorithm implementation, in particular the use of “Disjoint sets union” data structure with its heuristics “path compression” and “union be rank”, are investigated. A suitability of the algorithm for the use in automated systems is reviewed. An applicability of cluster validity measures for image segmentation quality assessment is analyzed.