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.
Wei, H., & Mao, J. (2018). The Recognition of Rice Area Images by UAV Based on Deep Learning. In MATEC Web of Conferences (Vol. 232). EDP Sciences. https://doi.org/10.1051/matecconf/201823202057