A concise review on food quality assessment using digital image processing
Background Recent advances in signal processing technology and computational power
have increased the attention towards computer vision-based techniques in diverse …
have increased the attention towards computer vision-based techniques in diverse …
[HTML][HTML] Computer vision based food grain classification: A comprehensive survey
This manuscript presents a comprehensive survey on recent computer vision based food
grain classification techniques. It includes state-of-the-art approaches intended for different …
grain classification techniques. It includes state-of-the-art approaches intended for different …
Deep learning based soybean seed classification
Z Huang, R Wang, Y Cao, S Zheng, Y Teng… - … and Electronics in …, 2022 - Elsevier
Accurately sorting high-quality soybean seeds is a crucial and time-consuming task in
quality inspection and food safety. This paper designs a full pipeline to classify the soybean …
quality inspection and food safety. This paper designs a full pipeline to classify the soybean …
Defect detection in fruit and vegetables by using machine vision systems and image processing
M Soltani Firouz, H Sardari - Food Engineering Reviews, 2022 - Springer
Today in the agricultural industry, many defects affect production efficiency; this paper aims
to show how the combination of machine vision (MV) and image processing (IP) helps to …
to show how the combination of machine vision (MV) and image processing (IP) helps to …
Identifying rice grains using image analysis and sparse-representation-based classification
Rice (Oryza sativa L.) is a major staple food worldwide, and is traded extensively. The
objective of this study is to distinguish the rice grains of 30 varieties nondestructively using …
objective of this study is to distinguish the rice grains of 30 varieties nondestructively using …
Varietal classification of barley by convolutional neural networks
Highlights•Deep learning and transfer learning CNNs are compared in barley varietal
classification.•Simplifying the CNN model has positive impact on classification results.•Only …
classification.•Simplifying the CNN model has positive impact on classification results.•Only …
Discrimination of gluten-free oats from contaminants using near infrared hyperspectral imaging technique
C Erkinbaev, K Henderson, J Paliwal - Food Control, 2017 - Elsevier
Oat is considered as a good addition to the gluten-free diet, but it is a challenge to keep the
oats segregated from other gluten-rich grains, such as wheat, barley, and rye. Therefore, oat …
oats segregated from other gluten-rich grains, such as wheat, barley, and rye. Therefore, oat …
Identifying barley varieties by computer vision
Visual discrimination between barley varieties is difficult, and it requires training and
experience. The development of automatic methods based on computer vision could have …
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 …
as a tool for classification, designed to identify apple orchard pests. The paper presents a …
Discriminating rapeseed varieties using computer vision and machine learning
F Kurtulmuş, H Ünal - Expert Systems with Applications, 2015 - Elsevier
Rapeseed is widely cultivated throughout the world for the production of animal feed,
vegetable fat for human consumption, and biodiesel. Since the seeds are evaluated in many …
vegetable fat for human consumption, and biodiesel. Since the seeds are evaluated in many …