Computer vision applied to food and agricultural products
ABSTRACT Computer vision (CV) has been applied for years to automate many human activities. It is one of the key technologies for the modernization of the agri-food industry towards the fourth industrial revolution (Industry 4.0). In the agricultural sector, CV systems are applied to automate or obt...
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Published in | Ciência agronômica Vol. 51; no. 5 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Universidade Federal do Ceará
01.01.2020
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Abstract | ABSTRACT Computer vision (CV) has been applied for years to automate many human activities. It is one of the key technologies for the modernization of the agri-food industry towards the fourth industrial revolution (Industry 4.0). In the agricultural sector, CV systems are applied to automate or obtain information from many agricultural tasks such as planting, cultivation, farm management, disease control, weed control or robotic harvesting. It is also widely used in postharvest to automate and obtain objective information in processes such as quality control and evaluation, damage detection, classification of fruits or vegetables in commercial categories or composition analysis. One of the main advantages is the ability of this technology to obtain information in regions of the spectrum that are invisible to the human eye. An example is the case of hyperspectral imaging systems. These systems generate a large amount of data that needs to be processed efficiently, creating robust and repeatable statistical models that allow the technology to be implemented at an industrial level. To achieve this, it is necessary to couple CV systems with advanced artificial intelligence tools such as machine learning or deep learning. The objective of this work is to review the latest advances in CV systems applied to food and agricultural products and processes. |
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AbstractList | ABSTRACT Computer vision (CV) has been applied for years to automate many human activities. It is one of the key technologies for the modernization of the agri-food industry towards the fourth industrial revolution (Industry 4.0). In the agricultural sector, CV systems are applied to automate or obtain information from many agricultural tasks such as planting, cultivation, farm management, disease control, weed control or robotic harvesting. It is also widely used in postharvest to automate and obtain objective information in processes such as quality control and evaluation, damage detection, classification of fruits or vegetables in commercial categories or composition analysis. One of the main advantages is the ability of this technology to obtain information in regions of the spectrum that are invisible to the human eye. An example is the case of hyperspectral imaging systems. These systems generate a large amount of data that needs to be processed efficiently, creating robust and repeatable statistical models that allow the technology to be implemented at an industrial level. To achieve this, it is necessary to couple CV systems with advanced artificial intelligence tools such as machine learning or deep learning. The objective of this work is to review the latest advances in CV systems applied to food and agricultural products and processes. |
Author | Pavarin, Fernanda Fernandes Adimari Castro, Wilson Fracarolli, Juliana Aparecida Blasco, Jose |
AuthorAffiliation | Instituto Valenciano de Investigaciones Agrarias/IVIA Universidad Nacional de Frontera Universidade Estadual de Campinas |
AuthorAffiliation_xml | – name: Instituto Valenciano de Investigaciones Agrarias/IVIA – name: Universidad Nacional de Frontera – name: Universidade Estadual de Campinas |
Author_xml | – sequence: 1 givenname: Juliana Aparecida surname: Fracarolli fullname: Fracarolli, Juliana Aparecida – sequence: 2 givenname: Fernanda Fernandes Adimari surname: Pavarin fullname: Pavarin, Fernanda Fernandes Adimari – sequence: 3 givenname: Wilson surname: Castro fullname: Castro, Wilson – sequence: 4 givenname: Jose surname: Blasco fullname: Blasco, Jose |
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ContentType | Journal Article |
Copyright | This work is licensed under a Creative Commons Attribution 4.0 International License. |
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DocumentTitleAlternate | Visão computacional aplicada a alimentos e produtos agrícolas |
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Keywords | Visão de máquina Digital images Machine vision Agriculture 4.0 Machine learning Inteligência artificial Aprendizado de máquina Agricultura 4.0 Artificial intelligence Imagens digitais |
Language | English |
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