Path: Top -> Journal -> Telkomnika -> 2018 -> Vol. 16, No. 4, August

Training of Convolutional Neural Network using Transfer Learning for Aedes Aegypti Larvae

Journal from gdlhub / 2018-07-26 11:44:07
By : Mohamad Aqil Mohd Fuad, Mohd Ruddin Ab Ghani, Rozaimi Ghazali, Tarmizi Ahmad Izzuddin, Mohamad Fani Sulaima, Zanariah Jano, Tole Sutikno, Telkomnika
Created : 2018-07-26, with 1 files

Keyword : transfer learning, inception V3, Aedes Aegypti larvae, water storage tank
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/8744
Document Source : WEB

The flavivirus epidemiology has reached an alarming rate which haunts the world population including Malaysia. World Health Organization has proposed and practised various methods of vector control through environmental management, chemical and biological orientations. However, from the listed control vectors, the most crucial part to be heeded are non-accessible places like water storage and artificial container. The objective of the study was to acquire and compare various accuracies and cross-entropy errors of the training sets within different learning rates in water storage tank environment which was essential for detection. This experiment performed transfer learning where Inception-V3 was implemented. About 534 images were trained to classify between Aedes Aegypti larvae and float valve within 3 different learning rates. For training accuracy and validation accuracy, learning rates were 0.1; 99.98%, 99.90% and 0.01; 99.91%, 99.77% and 0.001; 99.10%, 99.93%. Cross-entropy errors for training and validation for 0.1 were 0.0021, 0.0184 whereas for 0.01 were 0.0091, 0.0121 and 0.001; 0.0513, 0.0330. Various accuracies and cross-entropy errors of the training sets within the different learning rates were successfully acquired and compared.

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Publisher IDgdlhub
OrganizationTelkomnika
Contact NameHerti Yani, S.Kom
AddressJln. Jenderal Sudirman
CityJambi
RegionJambi
CountryIndonesia
Phone0741-35095
Fax0741-35093
Administrator E-mailelibrarystikom@gmail.com
CKO E-mailelibrarystikom@gmail.com

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