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 …
Current and future applications of statistical machine learning algorithms for agricultural machine vision systems
With being rapid increasing population in worldwide, the need for satisfactory level of crop
production with decreased amount of agricultural lands. Machine vision would ensure the …
production with decreased amount of agricultural lands. Machine vision would ensure the …
Principles, developments and applications of computer vision for external quality inspection of fruits and vegetables: A review
B Zhang, W Huang, J Li, C Zhao, S Fan, J Wu… - Food Research …, 2014 - Elsevier
Appearance is a very important sensory quality attribute of fruits and vegetables, which can
influence not only their market value, consumer's preferences and choice but also their …
influence not only their market value, consumer's preferences and choice but also their …
A methodology for fresh tomato maturity detection using computer vision
P Wan, A Toudeshki, H Tan, R Ehsani - Computers and electronics in …, 2018 - Elsevier
Recent advancements in computer vision have provided opportunities for new applications
in agriculture. Accurate yield estimation of fruit and vegetable crops is very important for …
in agriculture. Accurate yield estimation of fruit and vegetable crops is very important for …
Bruise damage measurement and analysis of fresh horticultural produce—A review
UL Opara, PB Pathare - Postharvest Biology and Technology, 2014 - Elsevier
Bruising is the most common type of mechanical damage affecting fresh horticultural
produce, and reduces quality to the consumer and income to fruit and vegetable industries …
produce, and reduces quality to the consumer and income to fruit and vegetable industries …
Advances in machine vision applications for automatic inspection and quality evaluation of fruits and vegetables
Artificial vision systems are powerful tools for the automatic inspection of fruits and
vegetables. Typical target applications of such systems include grading, quality estimation …
vegetables. Typical target applications of such systems include grading, quality estimation …
Supervised pattern recognition in food analysis
LA Berrueta, RM Alonso-Salces, K Héberger - Journal of chromatography A, 2007 - Elsevier
Data analysis has become a fundamental task in analytical chemistry due to the great
quantity of analytical information provided by modern analytical instruments. Supervised …
quantity of analytical information provided by modern analytical instruments. Supervised …
[HTML][HTML] Computer vision-based apple grading for golden delicious apples based on surface features
In this paper, a computer vision-based algorithm for golden delicious apple grading is
proposed which works in six steps. Non-apple pixels as background are firstly removed from …
proposed which works in six steps. Non-apple pixels as background are firstly removed from …
Machine vision system for food grain quality evaluation: A review
Background Quality of pre-processed food grains is a critical aspect and a major decider of
market acceptability, storage stability, processing quality, and overall consumer acceptance …
market acceptability, storage stability, processing quality, and overall consumer acceptance …
Machine learning approach for forecasting crop yield based on climatic parameters
S Veenadhari, B Misra, CD Singh - … International Conference on …, 2014 - ieeexplore.ieee.org
With the impact of climate change in India, majority of the agricultural crops are being badly
affected interms of their performance over a period of last two decades. Predicting the crop …
affected interms of their performance over a period of last two decades. Predicting the crop …