Frontiers in Plant Science (Feb 2024)

A segmentation network for farmland ridge based on encoder-decoder architecture in combined with strip pooling module and ASPP

  • Qingqing Hong,
  • Qingqing Hong,
  • Qingqing Hong,
  • Yue Zhu,
  • Yue Zhu,
  • Yue Zhu,
  • Wei Liu,
  • Wei Liu,
  • Wei Liu,
  • Tianyu Ren,
  • Tianyu Ren,
  • Tianyu Ren,
  • Changrong Shi,
  • Changrong Shi,
  • Changrong Shi,
  • Zhixin Lu,
  • Zhixin Lu,
  • Zhixin Lu,
  • Yunqin Yang,
  • Yunqin Yang,
  • Yunqin Yang,
  • Ruiting Deng,
  • Ruiting Deng,
  • Ruiting Deng,
  • Jing Qian,
  • Jing Qian,
  • Jing Qian,
  • Changwei Tan,
  • Changwei Tan,
  • Changwei Tan

DOI
https://doi.org/10.3389/fpls.2024.1328075
Journal volume & issue
Vol. 15

Abstract

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In order to effectively support wheat breeding, farmland ridge segmentation can be used to visualize the size and spacing of a wheat field. At the same time, accurate ridge information collecting can deliver useful data support for farmland management. However, in the farming ridge segmentation scenarios based on remote sensing photos, the commonly used semantic segmentation methods tend to overlook the ridge edges and ridge strip features, which impair the segmentation effect. In order to efficiently collect ridge information, this paper proposes a segmentation method based on encoder-decoder of network with strip pooling module and ASPP module. First, in order to extract context information for multi-scale features, ASPP module are integrated in the deepest feature map. Second, the remote dependence of the ridge features is improved in both horizontal and vertical directions by using the strip pooling module. The final segmentation map is generated by fusing the boundary features and semantic features using an encoder and decoder architecture. As a result, the accuracy of the proposed method in the validation set is 98.0% and mIoU is 94.6%. The results of the experiments demonstrate that the method suggested in this paper can precisely segment the ridge information, as well as its value in obtaining data on the distribution of farmland and its potential for practical application.

Keywords