Generolo Jono Žemaičio Lietuvos karo akademija

This research tackles the challenge of precisely segmenting military and army objects within intricate visual environments that are influenced by factors such as camouflage, clutter, occlusions, and variations in lighting. A hybrid framework is introduced that merges Graph Cut-based energy minimization with traditional image processing techniques and pre-detection using convolutional neural networks. This method combines appearance characteristics and spatial constraints to enhance robustness and the accuracy of boundaries. Results from experiments on significant military datasets indicate improved segmentation consistency and clarity, rendering the approach suitable for image analysis tasks that are critical for safety and defense.

The green economy is one of the important tools to ensure the sustainable development of any country. Green economy is defined as an economy with a high level of quality of life of the population, careful and rational use of natural resources in the interests of present and future generations and in accordance with the country’s international environmental obligations. The paper tackles a case of Kazakhstan. New policy towards green economy, as it is claimed, provides the basis for deep systemic reforms to improve the welfare, quality of life of the population of Kazakhstan and the country’s entry into a list of the 50 most developed countries in the world. In modern conditions, the relationship of economic development with changes in the environment, the impact on many forms of international economic relations is an important feature of the globalization of the economy. One of the most pressing issues among the international community is the issue of introducing a green economy, which is a reliable driving force of economic growth in emerging markets, providing new opportunities of overcoming the economic crisis. The paper analyzes efforts of Kazakhstan trough its active economic policy to transform its economy into green one.