Applications of computer vision for assessing quality of agri-food products: a review of recent research advances

J Ma, DW Sun, JH Qu, D Liu, H Pu… - Critical reviews in …, 2016 - Taylor & Francis
With consumer concerns increasing over food quality and safety, the food industry has
begun to pay much more attention to the development of rapid and reliable food-evaluation …

[HTML][HTML] Classification of fermented cocoa beans (cut test) using computer vision

MM Oliveira, BV Cerqueira, S Barbon Jr… - Journal of Food …, 2021 - Elsevier
Fermentation of cocoa beans is a critical step for chocolate manufacturing, since
fermentation influences the development of flavour, affecting components such as free …

Review of seed quality and safety tests using optical sensing technologies

M Huang, QG Wang, QB Zhu, JW Qin… - Seed Science and …, 2015 - ingentaconnect.com
Seeds are of great importance to agricultural and industrial production. As such, rapid and
non-destructive detection methods must be developed for the industry and consumers to …

Automatic inspection machine for maize kernels based on deep convolutional neural networks

C Ni, D Wang, R Vinson, M Holmes, Y Tao - Biosystems engineering, 2019 - Elsevier
Highlights•Design a dual-camera based synchronised maize inspection machine.•Applied
an improved background removal method.•Propose a K-means-guided curvature method to …

Varietal classification of barley by convolutional neural networks

M Kozłowski, P Górecki, PM Szczypiński - Biosystems Engineering, 2019 - Elsevier
Highlights•Deep learning and transfer learning CNNs are compared in barley varietal
classification.•Simplifying the CNN model has positive impact on classification results.•Only …

[HTML][HTML] Wheat varieties identification based on a deep learning approach

K Laabassi, MA Belarbi, S Mahmoudi… - Journal of the Saudi …, 2021 - Elsevier
Wheat variety recognition and authentication are essential tasks of the quality assessment in
the grain chain industry, especially for seed testing and certification processes. Recognition …

Identifying barley varieties by computer vision

PM Szczypiński, A Klepaczko, P Zapotoczny - Computers and Electronics in …, 2015 - Elsevier
Visual discrimination between barley varieties is difficult, and it requires training and
experience. The development of automatic methods based on computer vision could have …

Neural identification of selected apple pests

P Boniecki, K Koszela, H Piekarska-Boniecka… - … and Electronics in …, 2015 - Elsevier
The subject of this study was to investigate the possibility of using artificial neural networks
as a tool for classification, designed to identify apple orchard pests. The paper presents a …

Identifying defects and varieties of Malting Barley Kernels

M Kozłowski, PM Szczypiński, J Reiner, P Lampa… - Scientific Reports, 2024 - nature.com
This study introduces a comprehensive approach for classifying individual malting barley
kernels, involving dual-sided kernel imaging, a specifically designed image processing …

Detection of the granary weevil based on X-ray images of damaged wheat kernels

P Boniecki, H Piekarska-Boniecka… - Journal of Stored …, 2014 - Elsevier
Grain in storage is exposed to a number of adverse factors, including extensive damage to
grain kernels caused by infestations of the granary weevil Sitophilus granarius. This pest …