Issue |
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
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Article Number | 02057 | |
Number of page(s) | 5 | |
Section | 3D Images Reconstruction and Virtual System | |
DOI | https://doi.org/10.1051/matecconf/201823202057 | |
Published online | 19 November 2018 |
The Recognition of Rice Area Images by UAV Based on Deep Learning
School of mechanical and automotive engineering,Shanghai University Of Engineering Science, Shang hai 201620
Aiming at the target detection of remote sensing rice field of uav, the image of large-size uav is firstly segmented, and the type of each image is manually identified, and the image training set and verification set are made. Then, the training model of convolutional neural network is realized by python programming. The advantage and disadvantage of the two-layer convolutional neural network and ResNet50 are compared, and it is found that the training set is less and the picture feature complexity is not high in practical application. In the end, the feature recognition of rice field is realized, which has certain application value.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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