Aziguli Wulamu1,2,*, Jingyue Sang3, Dezheng Zhang1,2, Zuxian Shi1,2
Journal of New Media, Vol.2, No.4, pp. 149-155, 2020, DOI:10.32604/jnm.2020.014115
- 23 December 2020
Abstract Cultivated land extraction is essential for sustainable development and
agriculture. In this paper, the network we propose is based on the encoderdecoder structure, which extracts the semantic segmentation neural network of
cultivated land from satellite images and uses it for agricultural automation
solutions. The encoder consists of two part: the first is the modified Xception, it
can used as the feature extraction network, and the second is the atrous
convolution, it can used to expand the receptive field and the context information
to extract richer feature information. The decoder part uses the conventional
upsampling operation More >
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