Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Adedamola Wuraola"'
Autor:
Robin J. L. Hartley, Sadeepa Jayathunga, Peter D. Massam, Dilshan De Silva, Honey Jane Estarija, Sam J. Davidson, Adedamola Wuraola, Grant D. Pearse
Publikováno v:
Remote Sensing, Vol 14, Iss 14, p 3344 (2022)
Phenotyping has been a reality for aiding the selection of optimal crops for specific environments for decades in various horticultural industries. However, until recently, phenotyping was less accessible to tree breeders due to the size of the crop,
Externí odkaz:
https://doaj.org/article/ef56642e946440e79cb04959ae58aa5c
Autor:
Adedamola Wuraola, Nitish Patel
Publikováno v:
Neurocomputing. 482:163-185
Publikováno v:
Neurocomputing. 442:73-88
The importance of the choice of the activation function for training and inferencing in machine learning cannot be overemphasized. Activation functions can influence network training convergence, performance accuracy, and can make training and infere
Autor:
Nitish Patel, Adedamola Wuraola
Publikováno v:
IJCNN
A new activation function is proposed. This activation function uses the square operator to introduce the required non-linearity as compared with the use of an exponential term in the popular TanSig. Smaller computational operation count characterize
Autor:
Nitish Patel, Adedamola Wuraola
Publikováno v:
Neural Information Processing ISBN: 9783030041786
ICONIP (2)
ICONIP (2)
Strategically injected noise can speed up convergence during Neural Network training using backpropagation algorithm. Noise injection during Neural Network training have been proven empirically to improve convergence and generalizability. In this wor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::45035d0b965c973530fae9a4e3aa0459
https://doi.org/10.1007/978-3-030-04179-3_52
https://doi.org/10.1007/978-3-030-04179-3_52
Autor:
Nitish Patel, Adedamola Wuraola
Publikováno v:
Neural Information Processing ISBN: 9783030041786
ICONIP (2)
ICONIP (2)
We introduced a Square-law based RBF kernel called SQuare RBF (SQ-RBF) which is computationally efficient and effective due to the elimination of the exponential term. In contrast to the Gaussian RBF, SQ-RBF requires smaller computational operation c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9f3f718c97942ddf957426a3787ad7c
https://doi.org/10.1007/978-3-030-04179-3_9
https://doi.org/10.1007/978-3-030-04179-3_9
Publikováno v:
International Journal of P2P Network Trends and Technology. 14:16-20