Computer vision based food grain classification: A comprehensive survey

Classifying maize kernels naturally infected by fungi using near-infrared hyperspectral imaging

(2020) Xuan Chu et al.   INFRARED PHYSICS & TECHNOLOGY

Training instance segmentation neural network with synthetic datasets for crop seed phenotyping

(2020) Yosuke Toda et al.   Communications Biology

Near Infrared Hyperspectral Imaging for White Maize Classification According to Grading Regulations

(2019) Kate Sendin et al.   Food Analytical Methods

Varietal classification of barley by convolutional neural networks

(2019) Michał Kozłowski et al.   BIOSYSTEMS ENGINEERING

Identification of haploid and diploid maize seeds using convolutional neural networks and a transfer learning approach

(2019) Yahya Altuntaş et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Quality and Defect Inspection of Green Coffee Beans Using a Computer Vision System

(2019) García et al.   Applied Sciences-Basel

Maize seed classification using hyperspectral image coupled with multi-linear discriminant analysis

(2019) Chao Xia et al.   INFRARED PHYSICS & TECHNOLOGY

A Deep Convolutional Neural Network Architecture for Boosting Image Discrimination Accuracy of Rice Species

(2018) P. Lin et al.   Food and Bioprocess Technology

Classification of white maize defects with multispectral imaging

(2018) Kate Sendin et al.   FOOD CHEMISTRY

Wheat ear counting in-field conditions: high throughput and low-cost approach using RGB images

(2018) Jose A. Fernandez-Gallego et al.   Plant Methods

Variety Identification of Single Rice Seed Using Hyperspectral Imaging Combined with Convolutional Neural Network

(2018) Zhengjun Qiu et al.   Applied Sciences-Basel

Hyperspectral Image-Based Variety Classification of Waxy Maize Seeds by the t-SNE Model and Procrustes Analysis

(2018) Aimin Miao et al.   SENSORS

Detection Potential of Multi-Features Representation of E-Nose Data in Classification of Moldy Maize Samples

(2017) Yong Yin et al.   Food and Bioprocess Technology

MugNet: Deep learning for hyperspectral image classification using limited samples

(2017) Bin Pan et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Evaluation of the SeedCounter, A Mobile Application for Grain Phenotyping

(2017) Evgenii Komyshev et al.   Frontiers in Plant Science

A two-camera machine vision approach to separating and identifying laboratory sprouted wheat kernels

(2016) Bijay L. Shrestha et al.   BIOSYSTEMS ENGINEERING

Wheat grain classification by using dense SIFT features with SVM classifier

(2016) Murat Olgun et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Efficient technique for rice grain classification using back-propagation neural network and wavelet decomposition

(2016) Ksh. Robert Singh et al.   IET Computer Vision

Online Variety Discrimination of Rice Seeds Using Multispectral Imaging and Chemometric Methods

(2016) W. Liu et al.   Journal of Applied Spectroscopy

Computer vision-based method for classification of wheat grains using artificial neural network

(2016) Kadir Sabanci et al.   JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE

Maize Seed Variety Classification Using the Integration of Spectral and Image Features Combined with Feature Transformation Based on Hyperspectral Imaging

(2016) Min Huang et al.   Applied Sciences-Basel

Cereal Grain Classification by Optimal Features and Intelligent Classifiers

(2016) Ali Douik et al.   International Journal of Computers Communications & Control

Identifying barley varieties by computer vision

(2015) Piotr M. Szczypiński et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

A hybrid intelligent approach based on computer vision and fuzzy logic for quality measurement of milled rice

(2015) Hemad Zareiforoush et al.   MEASUREMENT

Computer vision technology determines optimal physical parameters for sorting JinDan 73 maize seeds

(2015) K.X. Wen et al.   SEED SCIENCE AND TECHNOLOGY

Evaluation and analysis the chalkiness of connected rice kernels based on image processing technology and support vector machine

(2014) Chengming Sun et al.   JOURNAL OF CEREAL SCIENCE

Nondestructive determination of transgenic Bacillus thuringiensis rice seeds (Oryza sativa L.) using multispectral imaging and chemometric methods

(2013) Changhong Liu et al.   FOOD CHEMISTRY

Automatic classification of non-touching cereal grains in digital images using limited morphological and color features

(2012) H.K. Mebatsion et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

A machine vision system for classification of wheat and barley grain kernels

(2011) F. Guevara-Hernandez et al.   SPANISH JOURNAL OF AGRICULTURAL RESEARCH

Classification of cereal grains using wavelet, morphological, colour, and textural features of non-touching kernel images

(2008) R. Choudhary et al.   BIOSYSTEMS ENGINEERING

Application of image analysis for the varietal classification of barley:

(2007) Piotr Zapotoczny et al.   JOURNAL OF CEREAL SCIENCE