MOESM4 of Panicle-SEG: a robust image segmentation method for rice panicles in the field based on deep learning and superpixel optimization

Xiong, Xiong; Duan, Lingfeng; Liu, Lingbo; Tu, Haifu; Yang, Peng; Wu, Dan; Chen, Guoxing; Xiong, Lizhong; Yang, Wanneng; Liu, Qian

doi:10.6084/m9.figshare.5639560.v1

13007_2017_254_MOESM4_ESM.docx (30.08 kB)

MOESM4 of Panicle-SEG: a robust image segmentation method for rice panicles in the field based on deep learning and superpixel optimization

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posted on 2017-11-28, 05:00 authored by Xiong Xiong, Lingfeng Duan, Lingbo Liu, Haifu Tu, Peng Yang, Dan Wu, Guoxing Chen, Lizhong Xiong, Wanneng Yang, Qian Liu

Additional file 4: Table S2. The evaluation criterion for 48 testing rice samples using four different segmentation algorithms.

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Rice (O. sativa) panicles Image segmentation Deep learning Convolutional neural network Superpixel

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MOESM4 of Panicle-SEG: a robust image segmentation method for rice panicles in the field based on deep learning and superpixel optimization

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