[HTML][HTML] Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review
Non-destructive testing techniques have gained importance in monitoring food quality over
the years. Hyperspectral imaging is one of the important non-destructive quality testing …
the years. Hyperspectral imaging is one of the important non-destructive quality testing …
Remote sensing in field crop monitoring: A comprehensive review of sensor systems, data analyses and recent advances
The key elements that underpin food security require the adaptation of agricultural systems
to support productivity increases while minimizing inputs and the adverse effects of climate …
to support productivity increases while minimizing inputs and the adverse effects of climate …
Hyperspectral imaging technology for quality and safety evaluation of horticultural products: A review and celebration of the past 20-year progress
In the past 20 years, hyperspectral imaging has been widely investigated as an emerging,
promising technology for evaluating quality and safety of horticultural products. This …
promising technology for evaluating quality and safety of horticultural products. This …
Modelling techniques to improve the quality of food using artificial intelligence
V Sahni, S Srivastava, R Khan - Journal of Food Quality, 2021 - Wiley Online Library
Artificial intelligence (AI), or AI/machine vision, is assuming an overwhelming part in the
realm of food handling and quality affirmation. As indicated by Mordor Intelligence, AI in the …
realm of food handling and quality affirmation. As indicated by Mordor Intelligence, AI in the …
Development of deep learning method for predicting firmness and soluble solid content of postharvest Korla fragrant pear using Vis/NIR hyperspectral reflectance …
The objective of this research was to develop a deep learning method which consisted of
stacked auto-encoders (SAE) and fully-connected neural network (FNN) for predicting …
stacked auto-encoders (SAE) and fully-connected neural network (FNN) for predicting …
Hyperspectral imagery applications for precision agriculture-a systemic survey
Hyperspectral imaging has been extensively investigated as an emerging, promising
technique for measuring the quality and protection of horticultural and agricultural products …
technique for measuring the quality and protection of horticultural and agricultural products …
Machine learning ensemble with image processing for pest identification and classification in field crops
T Kasinathan, SR Uyyala - Neural Computing and Applications, 2021 - Springer
In agriculture field, yield loss is a major problem due to attack of various insects in field
crops. Traditional insect identification and classification methods are time-consuming and …
crops. Traditional insect identification and classification methods are time-consuming and …
Multispectral imaging for plant food quality analysis and visualization
The multispectral imaging technique is considered a reformation of hyperspectral imaging. It
can be employed to noninvasively and rapidly evaluate food quality. Even though several …
can be employed to noninvasively and rapidly evaluate food quality. Even though several …
Non-destructive technologies for detecting insect infestation in fruits and vegetables under postharvest conditions: A critical review
In the last two decades, food scientists have attempted to develop new technologies that can
improve the detection of insect infestation in fruits and vegetables under postharvest …
improve the detection of insect infestation in fruits and vegetables under postharvest …
Ensemble feature selection for plant phenoty**: a journey from hyperspectral to multispectral imaging
Hyperspectral imaging is becoming an increasingly popular tool for high-throughput plant
phenoty**, because it provides remarkable insights about the health status of plants …
phenoty**, because it provides remarkable insights about the health status of plants …