Automated Detection Type Body and Shape Deformation for Robotic Welding Line

Author(s):  
Pavol Božek
2014 ◽  
Vol 29 (9) ◽  
pp. 661-667 ◽  
Author(s):  
S. Yamane ◽  
T. Godo ◽  
K. Hosoya ◽  
T. Nakajima ◽  
H. Yamamoto
Keyword(s):  

2013 ◽  
Vol 31 (3) ◽  
pp. 175-180 ◽  
Author(s):  
S. YAMANE ◽  
T. GODO ◽  
K. HOSOYA ◽  
T. NAKAJIMA ◽  
H. YAMAMOTO
Keyword(s):  

2012 ◽  
Vol 50 (05) ◽  
Author(s):  
G Valcz ◽  
I Bándi ◽  
B Wichmann ◽  
A Patai ◽  
D Szabó ◽  
...  

2004 ◽  
Author(s):  
A. Afshari ◽  
J. Antonini ◽  
S. Stone ◽  
G. Fletcher ◽  
V. Castranova ◽  
...  

2019 ◽  
Vol 2019 (1) ◽  
pp. 44-49
Author(s):  
S. Keitel ◽  
◽  
U. Mückenheim ◽  
U. Wolski ◽  
S. Lotz ◽  
...  
Keyword(s):  

Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.


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