Deep Learning Segmentation in Bulk Grain Images for Prediction of Grain Market Quality

Images, features, or feature distributions? A comparison of inputs for training convolutional neural networks to classify lentil and field pea milling fractions

(2021) Linda S. McDonald et al.   BIOSYSTEMS ENGINEERING

Prediction of milling yield in wheat with the use of spectral, colour, shape, and morphological features

(2021) Sahand Assadzadeh et al.   BIOSYSTEMS ENGINEERING

A review of deep learning methods for semantic segmentation of remote sensing imagery

(2020) Xiaohui Yuan et al.   EXPERT SYSTEMS WITH APPLICATIONS

Semantic versus instance segmentation in microscopic algae detection

(2019) Jesus Ruiz-Santaquiteria et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

High-Throughput Phenotyping of Seed/Seedling Evaluation Using Digital Image Analysis

(2018) Chongyuan Zhang et al.   Agronomy-Basel

A computer vision system for coffee beans classification based on computational intelligence techniques

(2016) Emanuelle Morais de Oliveira et al.   JOURNAL OF FOOD ENGINEERING

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features

(2016) Linda S. McDonald et al.   PLoS One

Image acquisition techniques for assessment of legume quality

(2015) Shveta Mahajan et al.   TRENDS IN FOOD SCIENCE & TECHNOLOGY

A digital image analysis method for assessment of lentil size traits

(2014) L.S. LeMasurier et al.   JOURNAL OF FOOD ENGINEERING

Morpho-colorimetric traits of Pisum seeds measured by an image analysis system

(2014) I. Smykalova et al.   SEED SCIENCE AND TECHNOLOGY

Discrimination of wheat grain varieties using image analysis and neural networks. Part I. Single kernel texture

(2011) Piotr Zapotoczny   JOURNAL OF CEREAL SCIENCE

Wheat class identification using monochrome images

(2007) A. Manickavasagan et al.   JOURNAL OF CEREAL SCIENCE