Maize seed variety identification using hyperspectral imaging and self-supervised learning: A two-stage training approach without spectral preprocessing

Author:

Zhang Liu,Zhang Shubin,Liu Jincun,Wei YaoguangORCID,An DongORCID,Wu Jianwei

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference50 articles.

1. Self-Supervised learning for data scarcity in a fatigue damage prognostic problem;Akrim;Engineering Applications of Artificial Intelligence,2023

2. Identification of haploid and diploid maize seeds using convolutional neural networks and a transfer learning approach;Altuntaş;Computers and Electronics in Agriculture,2019

3. Advances in infrared spectroscopy and hyperspectral imaging combined with artificial intelligence for the detection of cereals quality;An;Critical Reviews in Food Science and Nutrition,2022

4. Applications of hyperspectral imaging for quality assessment of liquid based and semi-liquid food products: A review;Baiano;Journal of Food Engineering,2017

5. Modular learning in neural networks;Ballard,1987

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