Background Recent advances in signal processing technology and computational power
have increased the attention towards computer vision-based techniques in diverse …

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 …

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 …

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 …

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 …

Highlights•Deep learning and transfer learning CNNs are compared in barley varietal
classification.•Simplifying the CNN model has positive impact on classification results.•Only …

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 …

Visual discrimination between barley varieties is difficult, and it requires training and
experience. The development of automatic methods based on computer vision could have …

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 …

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 …