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Tags: The VGG-16 convolutional neural network

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TELKOMNIKA Telecommunication, Computing, Electronics and Control
An improvement of Gram-negative bacteria identification using convolutional neural network with fine tuning

This paper proposes an image processing approach to identify Gram-negative bacteria. Gram-negative bacteria are one of the bacteria that cause lung lobe damage-bacterial samples obtained through smears of the patient's sputum. The first step…

Tags: Gram-negative bacteria,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , Graphics processing unit,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , Jurnal Nasional Informatika,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , Shape features,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , The VGG-16 convolutional neural network

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Browse Items (1 total)

TELKOMNIKA Telecommunication, Computing, Electronics and Control An improvement of Gram-negative bacteria identification using convolutional neural network with fine tuning

TELKOMNIKA Telecommunication, Computing, Electronics and Control
An improvement of Gram-negative bacteria identification using convolutional neural network with fine tuning