scholarly journals Traffic Supervision System Using Unmanned Aerial Vehicle based on Image Recognition Algorithm

2017 ◽  
pp. 573-584
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Image Recognition ◽  
Recognition Algorithm ◽  
Supervision System ◽  
Aerial Vehicle

The algorithm of the color signal recognition at landing an unmanned aerial vehicle on an aircraft carrier in autonomous mode

2020 ◽  
pp. 78
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Treatment Method ◽  
Recognition Algorithm ◽  
Connected Components ◽  
Preliminary Treatment ◽  
Signal Recognition ◽  
Aircraft Carrier ◽  
Halftone Image ◽  
Glide Path ◽  
Aerial Vehicle

The movement along the glide path of an unmanned aerial vehicle during landing on an aircraft carrier is investigated. The implementation of this task is realized in the conditions of radio silence of the aircraft carrier. The algorithm for treatment information from an optical landing system installed on an aircraft carrier is developed. The algorithm of the color signal recognition assumes the usage of the image frame preliminary treatment method via a downsample function, that performs the decimation process, the HSV model, the Otsu’s method for calculating the binarization threshold for a halftone image, and the method of separating the connected Two-Pass components. Keywords unmanned aerial vehicle; aircraft carrier; approach; glide path; optical landing system; color signal recognition algorithm; decimation; connected components; halftone image binarization

scholarly journals Method of landing UAV of helicopter type using an infrared camera

2016 ◽  
pp. 67-73
Author(s):  
K. V. Ivannikov ◽  
A. V. Gavrilov ◽  
A. S. Boev ◽  
I. S. Shoshin
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Infrared Camera ◽  
Recognition Algorithm ◽  
Bench Test ◽  
Program Complex ◽  
Infrared Emitters ◽  
Aerial Vehicle

The paper proposes using an infrared camera to detect the figure of a set of infrared emitters – guidance on the landing field. We developed an infrared guidance recognition algorithm and did its bench-test. Moreover, we made a program complex for modeling the landing field recognition during the landing of unmanned aerial vehicle (UAV) of helicopter type.

scholarly journals An Unmanned Aerial Vehicles Navigation System on the Basis of Pattern Recognition Applications

2020 ◽  
Vol 55 (3) ◽  
Author(s):  
Nidal Al Said ◽  
Yuri Gorbachev
Keyword(s):  
Pattern Recognition ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Navigation System ◽  
Electronic System ◽  
Recognition Algorithm ◽  
Navigation Systems ◽  
Pattern Recognition Algorithm ◽  
Analytical Review ◽  
Aerial Vehicle

In the presented paper, the authors substantiate the possibilities of creating a navigation system based on a pattern recognition algorithm. This system is exclusively based on the computing capabilities and memory of an onboard electronic system of an unmanned aerial vehicle. An analytical review and systematization are made of promising methods and algorithms for the implementation of pattern recognition applications based on alternative unmanned aerial vehicle navigation systems.

scholarly journals Multiscale Feature Filtering Network for Image Recognition System in Unmanned Aerial Vehicle

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xianghua Ma ◽  
Zhenkun Yang ◽  
Shining Chen
Keyword(s):  
Object Detection ◽  
Unmanned Aerial Vehicle ◽  
Image Recognition ◽  
Visual Recognition ◽  
Recognition System ◽  
Attention Mechanism ◽  
Feature Representation ◽  
Context Information ◽  
Aerial Vehicle ◽  
Feature Filtering

For unmanned aerial vehicle (UAV), object detection at different scales is an important component for the visual recognition. Recent advances in convolutional neural networks (CNNs) have demonstrated that attention mechanism remarkably enhances multiscale representation of CNNs. However, most existing multiscale feature representation methods simply employ several attention blocks in the attention mechanism to adaptively recalibrate the feature response, which overlooks the context information at a multiscale level. To solve this problem, a multiscale feature filtering network (MFFNet) is proposed in this paper for image recognition system in the UAV. A novel building block, namely, multiscale feature filtering (MFF) module, is proposed for ResNet-like backbones and it allows feature-selective learning for multiscale context information across multiparallel branches. These branches employ multiple atrous convolutions at different scales, respectively, and further adaptively generate channel-wise feature responses by emphasizing channel-wise dependencies. Experimental results on CIFAR100 and Tiny ImageNet datasets reflect that the MFFNet achieves very competitive results in comparison with previous baseline models. Further ablation experiments verify that the MFFNet can achieve consistent performance gains in image classification and object detection tasks.

scholarly journals A Newly Developed Unmanned Aerial Vehicle (UAV) Imagery Based Technology for Field Measurement of Water Level

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 124 ◽  
Author(s):  
Ang Gao ◽  
Shiqiang Wu ◽  
Fangfang Wang ◽  
Xiufeng Wu ◽  
Peng Xu ◽  
...  
Keyword(s):  
Water Level ◽  
Unmanned Aerial Vehicle ◽  
Image Recognition ◽  
Field Measurement ◽  
Correction Method ◽  
Water Levels ◽  
Parameter Calibration ◽  
Statistical Parameters ◽  
Aerial Vehicle ◽  
Measuring Section

Field measurement of water level is important for water conservancy project operation and hydrological forecasting. In this study, we proposed a new measuring technique by integrating the advantages of unmanned aerial vehicle (UAV) photogrammetry and image recognition technology. Firstly, the imagery of water fluctuation process was captured by an UAV airborne camera, and water surface line in the imagery was recognized and extracted using image recognition technology. Subsequently, successive water levels at a measuring section were calculated by parameter calibration. Statistical parameters of water levels, such as maximum, average, and minimum values during the capturing period were also calculated. Additionally, we introduced a correction method to offset the error caused by UAV drift. The newly proposed method was tested in field measurement for Miaowei hydropower station, China, and the results showed that the method is reliable and adoptable.

Study on Fault Diagnosis of Planetary Gearbox in Unmanned Aerial Vehicle Using Multi sensor Data

2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Unmanned Aerial Vehicle ◽  
Sensor Data ◽  
Planetary Gearbox ◽  
Aerial Vehicle

Results of Spatial Structure of Atmosphere Radiation in a Spectral Range (1.5–2) µm Research

2018 ◽  
pp. 7-13
Author(s):  
Anton M. Mishchenko ◽  
Sergei S. Rachkovsky ◽  
Vladimir A. Smolin ◽  
Igor V . Yakimenko
Keyword(s):  
Spatial Structure ◽  
Unmanned Aerial Vehicle ◽  
Wavelength Range ◽  
Spectral Range ◽  
Near Ir ◽  
Optoelectronic Systems ◽  
Aerial Vehicle

Results of experimental studying radiation spatial structure of atmosphere background nonuniformities and of an unmanned aerial vehicle being the detection object are presented. The question on a possibility of its detection using optoelectronic systems against the background of a cloudy field in the near IR wavelength range is also considered.

Positioning the Angle of Attack Sensor on an Unmanned Aerial Vehicle Wing

2016 ◽  
Vol 3 (1) ◽  
pp. 25-33
Author(s):  
Amir Birjandi ◽  
◽  
Valentin Guerry ◽  
Eric Bibeau ◽  
Hamidreza Bolandhemmat ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Angle Of Attack ◽  
Aerial Vehicle
Sign in / Sign up

Export Citation Format

Share Document