科研产出
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1A fast multi-source information fusion strategy based on deep learning for species identification of boletes
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机构：
来源：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
关键词： Boletes; Near-infrared; Two-dimensional correlation spectroscopy; Deep learning; Species identification
年份：2022
2Application of infrared spectroscopy combined with chemometrics in mushroom
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机构：
来源：APPLIED SPECTROSCOPY REVIEWS
关键词： Mushroom; infrared spectroscopy; chemometrics; qualitative analysis; quantitative analysis
3Rapid identification of total phenolic content levels in boletes by two-dimensional correlation spectroscopy combined with deep learning
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机构：
来源：VIBRATIONAL SPECTROSCOPY
关键词： Wild boletes; Total polyphenol content; High performance liquid chromatography; Fourier transform near -infrared; Residual convolutional neural network
年份：2022
4A geographical traceability method for Lanmaoa asiatica mushrooms from 20 township-level geographical origins by near infrared spectroscopy and ResNet image analysis techniques br
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机构：
来源：ECOLOGICAL INFORMATICS
关键词： Boletes; Near -infrared spectroscopy; Residual neural network; Geographical traceability; Key climate factors
年份：2022
5Small-scale districts identification of Boletus bainiugan from Yunnan province of China based on residual convolutional neural network continuous classification models
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机构：
来源：JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION
关键词： Small-scale districts; Geographical origin; Boletus bainiugan; FT-NIR; 2D-COS; ResNet
年份：2024
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