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Object Detection from the Video Taken by Drone via Convolutional Neural Networks
Joint Authors
Zhang, Yangyang
Sun, Chenfan
Zhan, Wei
She, Jinhiu
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-13
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The aim of this research is to show the implementation of object detection on drone videos using TensorFlow object detection API.
The function of the research is the recognition effect and performance of the popular target detection algorithm and feature extractor for recognizing people, trees, cars, and buildings from real-world video frames taken by drones.
The study found that using different target detection algorithms on the “normal” image (an ordinary camera) has different performance effects on the number of instances, detection accuracy, and performance consumption of the target and the application of the algorithm to the image data acquired by the drone is different.
Object detection is a key part of the realization of any robot’s complete autonomy, while unmanned aerial vehicles (UAVs) are a very active area of this field.
In order to explore the performance of the most advanced target detection algorithm in the image data captured by UAV, we have done a lot of experiments to solve our functional problems and compared two different types of representative of the most advanced convolution target detection systems, such as SSD and Faster R-CNN, with MobileNet, GoogleNet/Inception, and ResNet50 base feature extractors.
American Psychological Association (APA)
Sun, Chenfan& Zhan, Wei& She, Jinhiu& Zhang, Yangyang. 2020. Object Detection from the Video Taken by Drone via Convolutional Neural Networks. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1194867
Modern Language Association (MLA)
Sun, Chenfan…[et al.]. Object Detection from the Video Taken by Drone via Convolutional Neural Networks. Mathematical Problems in Engineering No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1194867
American Medical Association (AMA)
Sun, Chenfan& Zhan, Wei& She, Jinhiu& Zhang, Yangyang. Object Detection from the Video Taken by Drone via Convolutional Neural Networks. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1194867
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194867