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Rapid nondestructive detecting of sorghum varieties based on hyperspectral imaging and convolutional neural network

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Extraction of Spectral Information from Hyperspectral Data and Application of Hyperspectral Imaging for Food and Agricultural Products

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Identification of maize haploid kernels based on hyperspectral imaging technology

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Rapid and nondestructive detection of sorghum adulteration using optimization algorithms and hyperspectral imaging

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Rapid and nondestructive prediction of amylose and amylopectin contents in sorghum based on hyperspectral imaging

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Detection of fat content in peanut kernels based on chemometrics and hyperspectral imaging technology

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Hybrid convolutional network based on hyperspectral imaging for wheat seed varieties classification

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Machine learning modeling and prediction of peanut protein content based on spectral images and stoichiometry

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Combination of spectra and texture data of hyperspectral imaging for prediction and visualization of palmitic acid and oleic acid contents in lamb meat

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Classification of hybrid seeds using near-infrared hyperspectral imaging technology combined with deep learning

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Review of the most common pre-processing techniques for near-infrared spectra

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Support Vector Machines for classification and regression

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2008 Eighth IEEE International Conference on Data Mining

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Nearest Neighbor Classification of Remote Sensing Images With the Maximal Margin Principle

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Learning and Transferring Deep Joint Spectral–Spatial Features for Hyperspectral Classification

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IEEE Transactions on Geoscience and Remote Sensing

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Identification of soybean varieties based on hyperspectral imaging technology and one‐dimensional convolutional neural network

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Rapid and accurate detection of starch content in mixed sorghum by hyperspectral imaging combined with data fusion technology

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Identification of red jujube varieties based on hyperspectral imaging technology combined with CARS‐IRIV and SSA‐SVM

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ImageNet classification with deep convolutional neural networks

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Identification of Near Geographical Origin of Wolfberries by a Combination of Hyperspectral Imaging and Multi-Task Residual Fully Convolutional Network

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Rice Seed Cultivar Identification Using Near-Infrared Hyperspectral Imaging and Multivariate Data Analysis

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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Ginseng Seed Variety Identification Based on Hyperspectral Imaging Technology and Transfer Learning

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