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TELKOMNIKA Telecommunication, Computing, Electronics and Control
Image based anthracnose and red-rust leaf disease detection using deep learning
Deep residual learning frameworks have achieved great success in image
classification. This article presents the use of transfer learning which is
applied on mango leaf image dataset for its disease’s detection. New
methodology and training have…
classification. This article presents the use of transfer learning which is
applied on mango leaf image dataset for its disease’s detection. New
methodology and training have…
TELKOMNIKA Telecommunication Computing Electronics and Control
Quantum transfer learning for image classification
Quantum machine learning, an important element of quantum computing,
recently has gained research attention around the world. In this paper, we have
proposed a quantum machine learning model to classify images using a
quantum classifier. We…
recently has gained research attention around the world. In this paper, we have
proposed a quantum machine learning model to classify images using a
quantum classifier. We…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Handwriting identification using deep convolutional neural network method
Handwriting is a unique thing that produced differently for each person.
Handwriting has a characteristic that remain the same with single writer,
so a handwriting can be used as a variable in biometric systems. Each person have a different form of…
Handwriting has a characteristic that remain the same with single writer,
so a handwriting can be used as a variable in biometric systems. Each person have a different form of…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Transfer learning with multiple pre-trained network for fundus classification
Transfer learning (TL) is a technique of reuse and modify a pre-trained network. It reuses feature extraction layer at a pre-trained network. A target domain in TL obtains the features knowledge from the source domain. TL modified classification…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
UNet-VGG16 with transfer learning for MRI-based brain tumor segmentation
A brain tumor is one of a deadly disease that needs high accuracy in its
medical surgery. Brain tumor detection can be done through magnetic
resonance imaging (MRI). Image segmentation for the MRI brain tumor aims to separate the tumor area (as the…
medical surgery. Brain tumor detection can be done through magnetic
resonance imaging (MRI). Image segmentation for the MRI brain tumor aims to separate the tumor area (as the…