Evaluation of germination rate of tomato seeds with autonomous image processing and artificial neural networks system

2021 ◽  
pp. 303-310
Author(s):  
D. Stajnko ◽  
Č. Rozman ◽  
U. Škrubej
Agricultura ◽  
2015 ◽  
Vol 12 (1-2) ◽  
pp. 19-24
Author(s):  
Uroš Škrubej ◽  
Črtomir Rozman ◽  
Denis Stajnko

Abstract This paper describes a computer vision system based on image processing and machine learning techniques which was implemented for automatic assessment of the tomato seed germination rate. The entire system was built using open source applications Image J, Weka and their public Java classes and linked by our specially developed code. After object detection, we applied artificial neural networks (ANN), which was able to correctly classify 95.44% of germinated seeds of tomato (Solanum lycopersicum L.).


2020 ◽  
pp. 15-20
Author(s):  
K. Sujatha ◽  
V. Srividhya ◽  
V. Karthikeyan ◽  
L. Madheshwaran ◽  
N. P. G. Bhavani

2019 ◽  
Vol 6 (4) ◽  
pp. 253-256
Author(s):  
Chanwit Kaewtapee ◽  
◽  
Choawit Rakangtong ◽  
Chaiyapoom Bunchasak

1998 ◽  
Vol 7 (8) ◽  
pp. 1093-1096 ◽  
Author(s):  
R. Chellappa ◽  
K. Fukushima ◽  
A.K. Katsaggelos ◽  
Sun-Yuan Kung ◽  
Y. LeCun ◽  
...  

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