An integral automation of industrial fruit and vegetable sorting by machine vision

2002 ◽  
Author(s):  
F. Pla ◽  
J.M. Sanchiz ◽  
J.S. Sanchez
Keyword(s):  
Machine Vision ◽  
Fruit And Vegetable

Machine Vision-Based Fruit and Vegetable Disease Recognition: A Review

2021 ◽  
pp. 143-157
Author(s):  
Md. Tarek Habib ◽  
Md. Ariful Islam Arif ◽  
Sumaita Binte Shorif ◽  
Mohammad Shorif Uddin ◽  
Farruk Ahmed
Keyword(s):  
Machine Vision ◽  
Fruit And Vegetable

Machine Vision

2009 ◽  
Author(s):  
Wesley E. Snyder ◽  
Hairong Qi
Keyword(s):  
Machine Vision

Fruit and Vegetable Screening Measure

2004 ◽  
Author(s):  
Judith J. Prochaska ◽  
James F. Sallis
Keyword(s):  
Fruit And Vegetable ◽  
Screening Measure

Analysing capabilities and resources used to incorporate fruit and vegetables into the family diet: findings from an Australian case study

2014 ◽  
Vol 2 (1) ◽  
pp. 13
Author(s):  
Samantha B Meyer
Keyword(s):  
Low Income ◽  
Vegetable Intake ◽  
Vegetable Consumption ◽  
Fruit And Vegetables ◽  
Fruit And Vegetable ◽  
Organizational Skills ◽  
Australian Case ◽  
Low Income Families ◽  
Conducting Research

Research attributes low fruit and vegetable consumption to problems of access, availability and affordability. We conducted, for the first time, a case study with three families designed and analysed using the sustainable Livelihoods Framework. The benefit of such an approach is that we moved away from identified barriers and towards identifying the capabilities and resources low-income families use to incorporate fruit and vegetables into their diets. Mitigating cost and access, we provided families with a box of fresh fruit and vegetables free of charge for up to 10 weeks and observed and recorded how/if the contents were used. Results identify the importance of social networking, organizational skills, knowledge of health benefits, and social structures. This paper demonstrates an effective methodology for understanding the capabilities of, rather than barriers to, low-income families increasing fruit and vegetable intake. Additionally, we provide a ‘how to’ and ‘lessons from the field’ for researchers interested in conducting research of this nature.

Classroom Lighting Energy-Saving Control System Based on Machine Vision Technology

2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG
Keyword(s):  
Control System ◽  
Machine Vision ◽  
Energy Saving ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Lighting Control ◽  
Lighting Energy ◽  
Neural Network Algorithm ◽  
Energy Saving Control ◽  
Model Algorithm

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.

Fruit and vegetable biotechnology

2002 ◽  
Author(s):  
Victoriano Valpuesta
Keyword(s):  
Fruit And Vegetable

Machine Vision, Let's Go into the Street

1997 ◽  
Vol 117 (10) ◽  
pp. 1339-1344
Author(s):  
Katsuhiko Sakaue ◽  
Hiroyasu Koshimizu
Keyword(s):  
Machine Vision
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