Кафедра авіаційних комп'ютерно-інтегрованих комплексів (НОВА)

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Відповідальний за розділ: Провідний фахівець кафедри авіаційних комп'ютерно-інтегрованих комплексів інституту інформаційно-діагностичних систем Шугалєй Людмила Петрівна. E-mail: shugaley2005@ukr.net

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Browsing Кафедра авіаційних комп'ютерно-інтегрованих комплексів (НОВА) by Subject "004.93 (045)"

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    Image processing from unmanned aerial vehicle using modified YOLO detector
    (National Aviation University, 2021-12-21) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Kalmykov, Vadym; Калмиков, Вадим Віталійович
    Identifying objects from drone images is a state-of-the-art task for artificial neural networks. Since drones are always moving at different altitudes, the scale of the object varies greatly, making it difficult to optimize the networks. Moreover, flying at high speeds and low altitudes leads to blurred images of densely populated objects during movement, which is a problem when solving the problem of recognizing and classifying small sized objects. This paper addresses the above problem solutions and solves them by applying an additional prediction model to identify objects of different scales. We also modify the loss function to penalize larger objects more and vice versa to encourage recognition of smaller objects. To achieve improvements, we use advanced techniques such as multiscale testing, image blurring, object rotation, and data distortion. Experiments with a large data set show that our model has good performance in drone images. Compared to the baseline model (YOLOv5), our model shows significant improvements in object recognition and classification.
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    Intellectual system for printed circuit board manufacture dased on Mirae Mx-200
    (National Aviation University, 2021-10-21) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Plodystyy, Bogdan; Плодистий, Богдан Олександрович
    It is considered the main disadvantages of printed circuit boards manufacture based on the Mirae Mx-200 system. In order to reduce the level of manufacturing defects and increase productivity, it is proposed to include an intelligent unit based on the YOLO neural network in the system, which is implemented by an additional Raspberry controller included in the system. The YOLO neural network is used to process images obtained from an additionally installed video camera, which monitors the production process. In this work, based on the use of the solution to the classification problem, the problem of decision support is formulated and solved. As a result, the operations (actions) that need to be taken are determined: automatic centering, reset, cancel, etc. Using emulation with additional microcontroller connections, the problem of limited installer resources and the implementation of more complex algorithms in the installer's work is solved.
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    Intellectual system of preparation of images from computer tomographs
    (National Aviation University, 2021-01-05) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Kharchuk, Yaroslav; Харчук, Ярослав Володимирович
    Artificial neural networks can be trained on useful signals of the source data, but can not be taught on noisy data, so it is usually performed noise reduction or error compensation. This paper implements a noise reduction model based on artificial neural networks to suppress high-noise components, which is important for optimizing pre-filtering methods. The process of cleaning computers’ tomography scans in medical examinations of patients with tuberculosis is considered as an given problem in which the suppression of noise present in the image is required.. In order to reduce the level of radiation due to it is quite harmful to human. the power of the radiation is reduced. As a result, the ratio of the useful signal to noise is reduced, which causes noise, which contaminates the image and complicates its processing. Additional shadows appears on the image that no objects exist, which can provide false diagnosis. An algorithm for structural-parametric synthesis of convolutional neural networks used in image noise suppression has been developed. Computer tomograms of tuberculosis patients provided by the Research Institute of Pulmonology and Tuberculosis of the National Academy of Medical Sciences of Ukraine were used as a training sample.
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    System for detecting and analyzing textual information of product composition
    (National Aviation University, 2021-10-21) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Kozak, Olena; Козак, Олена Сергіївна
    The paper substantiates the need to obtain an assessment of the harm of food products for consumers with chronic diseases or allergies, which is important to prevent a possible worsening of the course of the disease or eliminate an acute allergic reaction of the human body to hazardous ingredients present in the product. It is proposed to use food labels and packaging as the primary sources of information about the food product that is available to the consumer. It is shown that, the printed information on the packages of Ukrainian food products meets the requirements of the law "On Consumer Information on Food Products" and the labeling on food labels is presented in the text-graphic form. In this work it is used convolution neural networks for text-graphic information processing. It is proposed and substantiated the system structure for detecting and analyzing the text-graphical information of product composition. It is developed mobile software solution.