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EN
The article describes recent object detection methods with their main advantages and drawbacks and shows results of application of machine learning Haar Cascade algorithm for automobile detection. The article underlines problems related to the feature dataset generation and presents an overview of current dataset augmentation methods such as image mirroring, cropping, rotating, shearing and color modification. New methods fot image dataset augmentation, such as utilization of CAD models and Deep Learning solutions, are also proposed. In order to ensure low cost, real time detection machine learning based Haar Cascade detector has been proposed and tested on a custom dataset specifically created for dataset augmentation methods evalutation. Article provides all input parameters for detector training process, along with a brief description of object detection metrics. Finally the article presents results of the baseline detector and augumented calssificator created based on vertical image mirroring technique, for different dataset configurations. Algorithms performance for real time detection on high resolution images was also evaluated.
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EN
The development of the global economy and increased competition requires organizations to find new ways to enhance their competitive advantage. The most important and powerful source of important benefits organizations now have the knowledge and study of the subject – knowledge management processes. The efficiency of knowledge management depends on how these processes are interrelated infrastructure and processes of the organization to support the achievement of its objectives. To understand these relationships and present, not a simple list of elements and processes of the organization. Thus, we can conclude that requires an integrated structure in which all integrated dynamic coherent whole.
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