The estimation of wildlife populations is an issue currently being solved at workplaces on many levels. Knowledge of wildlife population and localization is not only very important for reducing damage to agricultural and forest growth, which arises from the local overgrowth of certain animal species, but also for the protection of endangered species of animals and plants.The article presents the results of a research carried out during 2017 as the first partial objective of a complex automated wildlife estimation project, namely the recognition of game in a free landscape without vegetation cover from an UAV (unmanned aerial vehicle). The paper describes a method of finding game animals in a selected area and identifies problems with the recognition of the animals hiding in the vegetation. These results play an important role in solving the overall complex problem of automated game recognition.
This article presents the role of mind maps in creating well-structured elearning materials and courses, which has become very important with increasing influence of new technologies and alternative study modes. The basic principles of mind mapping are described, including structural components of mind maps, and examples of practical use cases. Based on the identified lack of existing methodical frameworks for creating interactive mind maps for e-learning, we present a set of rules and metrics, which can help to identify points of ineffectiveness, and eliminate redundancies. This framework for creating effective mind maps and its implications are described in details with help of illustrative figures and textual description. The maps that has been created in accordance with this methodology are clear and comprehensible.
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