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Maize Haploid Identification via LSTM-CNN and Hyperspectral Imaging Technology
In our study, the first attempt to design a high-accurate identification model of maize haploid seeds from diploid ones based on optimum waveband selection of the LSTM-CNN algorithm is realized via deep learning and hyperspectral imaging technology, with accuracy reaching 97% in the determining optimum waveband of 1367. 6-1526. 4nm.
Hyperspectral Imaging Technology and Transfer Learning Utilized in Identification Haploid Maize Seeds
The experimental results show that, CNN model which is pre-trained by visible light image database can be applied to the near-infrared hyperspectral imaging-based identification of maize seeds, and high accurate identification rate can be achieved.
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