Discrimination of tomato plants under different irrigation regimes: analysis of hyperspectral sensor data

2014 ◽  
Vol 26 (2) ◽  
pp. 77-88 ◽  
Author(s):  
M. Rinaldi ◽  
A. Castrignanò ◽  
D. De Benedetto ◽  
D. Sollitto ◽  
S. Ruggieri ◽  
...  
Author(s):  
Hiroshi P. SATO ◽  
Mamoru KOARAI ◽  
Satoshi MIYASAKA ◽  
Hajime MAKITA ◽  
Hiroshi YAGI

Author(s):  
Naoko KOSAKA ◽  
Yohei MINEKAWA ◽  
Kuniaki UTO ◽  
Yukio KOSUGI ◽  
Kunio ODA ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jing Liu ◽  
Tingting Wang ◽  
Yulong Qiao

Sensor data analysis is used in many application areas, for example, Artificial Intelligence of Things (AIoT), with the rapid developing of the deep neural network learning that promotes its application area. In this work, we propose the Depth and Width Changeable Deep Kernel Learning-based hyperspectral sensing data analysis algorithm. Compared with the traditional kernel learning-based hyperspectral data classification, the proposed method has its advantages on the hyperspectral data classification. With the deep kernel learning, the feature is mapped through many times mapping and has the more discriminative ability. So, the deep kernel learning has the better performance compared with the multiple kernels learning. And it has the ability to adjust the network architecture for hyperspectral data space, with the optimization equation of the span bound. The experiments are implemented to testified the feasibility and performance of the algorithms on the hyperspectral data analysis, with the classification accuracy of hyperspectral data. The comprehensive analysis of the experiments shows that the proposed algorithm is feasible to hyperspectral sensor data analysis and its promising classification method in many areas data analysis.


2013 ◽  
Vol 9 (10) ◽  
pp. 217180 ◽  
Author(s):  
Zebin Wu ◽  
Shun Ye ◽  
Jie Wei ◽  
Zhihui Wei ◽  
Le Sun ◽  
...  

2019 ◽  
Vol 4 (3) ◽  
pp. 181-205
Author(s):  
N.M. Malash ◽  
M.A. Fattahalla ◽  
Mona R. Khalil ◽  
Eman S. A. Ibrahim

2007 ◽  
Vol 30 (1-2) ◽  
pp. 97-108 ◽  
Author(s):  
Sindy Sterckx ◽  
Els Knaeps ◽  
Mark Bollen ◽  
Koen Trouw ◽  
Rik Houthuys

2019 ◽  
Vol 4 (3) ◽  
pp. 181-205
Author(s):  
N.M. Malash ◽  
M.A. Fattahalla ◽  
Mona R. Khalil ◽  
Eman S. A. Ibrahim

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