Development of a Hardware-Software System for the Assembled Helicopter-Type UAV Prototype by Applying Optimal Classification and Pattern Recognition Methods

Boranbayev, Askar; Boranbayev, Seilkhan; Nurbekov, Askar

doi:10.1007/978-3-030-52246-9_28

Cited by 8 publications

(2 citation statements)

References 17 publications

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“…A recently proposed face recognition model is based on a Viola–Jones algorithm and uses a sliding window method 22 . The model uses a small window moving over an image with a specified step size and a cascade of classifiers to detect the presence of a face within the window space.…”

Section: Analysis Results Of Methods and Discussionmentioning

confidence: 99%

“…21 A recently proposed face recognition model is based on a Viola-Jones algorithm and uses a sliding window method. 22 The model uses a small window moving over an image with a specified step size and a cascade of classifiers to detect the presence of a face within the window space. As it can be seen, the sliding window method is a simple and effective method of object recognition, which can also be employed in UAV's navigation systems.…”

Section: R E T R a C T E D F I G U R Ementioning

confidence: 99%

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Retracted: An unmanned aerial vehicles navigation system on the basis of pattern recognition applications—Review of implementation options and prospects for development

2021

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The popularity of unmanned aerial vehicles (UAVs) kept growing over the past few decades. UAVs are widely used in various fields for monitoring, mapping, aerial photography, rescue operations, and so forth. However, the UAV navigation may be difficult in areas where global positioning systems is not available. This article presents an analytical review of the promising methods of creating a navigation system based on a pattern recognition algorithm. Linear algebra and mathematical morphology to describe the operation of pattern recognition applications in UAV's navigation systems, classification of images through profound research of intelligent navigation systems, analysis and digital image processing to identify options for the implementation of artificial intelligent systems of visual navigation were used to identify existing pattern recognition applications in the process of constructive systematization. It was shown that the UAV navigation requires objects in the image to be recognized and the distance to a possible obstacle to be estimated using deep learning method for image segmentation and depth map estimation. An obligatory initial point in the image recognition algorithm is the image preprocessing procedures based on machine vision techniques. The results of this study may be useful in developing efficient UAV applications for military and civil purposes.

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Section: Analysis Results Of Methods and Discussionmentioning

confidence: 99%

Section: R E T R a C T E D F I G U R Ementioning

confidence: 99%