A Machine Vision for Tomato Cluster Harvesting Robot

2008 ◽  
Author(s):  
Naoshi Kondo ◽  
Kazuya Yamamoto ◽  
Koki Yata ◽  
Mitsutaka Kurita
Keyword(s):  
Machine Vision ◽  
Harvesting Robot

A Machine Vision System for Tomato Cluster Harvesting Robot

2009 ◽  
Vol 2 (2) ◽  
pp. 60-65 ◽  
Author(s):  
Naoshi Kondo ◽  
Kazuya Yamamoto ◽  
Hiroshi Shimizu ◽  
Koki Yata ◽  
Mitsutaka Kurita ◽  
...  
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Machine Vision System ◽  
Harvesting Robot

scholarly journals Machine vision for a selective broccoli harvesting robot

2016 ◽  
Vol 49 (16) ◽  
pp. 66-71 ◽  
Author(s):  
Pieter M. Blok ◽  
Ruud Barth ◽  
Wim van den Berg
Keyword(s):  
Machine Vision ◽  
Harvesting Robot

scholarly journals Using YOLOv3 Algorithm with Pre- and Post-Processing for Apple Detection in Fruit-Harvesting Robot

Agronomy ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1016 ◽  
Author(s):  
Anna Kuznetsova ◽  
Tatiana Maleva ◽  
Vladimir Soloviev
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Error Rates ◽  
Machine Vision System ◽  
Detection Time ◽  
Post Processing ◽  
Processing Techniques ◽  
Harvesting Robot ◽  
A Share

A machine vision system for detecting apples in orchards was developed. The system was designed to be used in harvesting robots and is based on a YOLOv3 algorithm with special pre- and post-processing. The proposed pre- and post-processing techniques made it possible to adapt the YOLOv3 algorithm to be used in an apple-harvesting robot machine vision system, providing an average apple detection time of 19 ms with a share of objects being mistaken for apples at 7.8% and a share of unrecognized apples at 9.2%. Both the average detection time and error rates are less than in all known similar systems. The system can operate not only in apple-harvesting robots but also in orange-harvesting robots.

2A1-B08 Machine Vision for a Tomato Fruit Cluster Harvesting Robot

2008 ◽  
Vol 2008 (0) ◽  
pp. _2A1-B08_1-_2A1-B08_4
Author(s):  
Noshi KONDO ◽  
Kazuya YAMAMOTO ◽  
Kouki YATA ◽  
Mitsutaka KURITA
Keyword(s):  
Machine Vision ◽  
Tomato Fruit ◽  
Harvesting Robot

Machine Vision

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

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.

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

Machine Vision Technologies to Connect with Humans

2005 ◽  
Vol 125 (11) ◽  
pp. 692-695
Author(s):  
Kazunori UMEDA ◽  
Yoshimitsu AOKI
Keyword(s):  
Machine Vision
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