Rapid bacterial colony classification using deep learning

Son Ali Akbar, Kawarul Hawari Ghazali, Habsah Hasan, Zeehaida Mohamed, Wahyu Sapto Aji, Anton Yudhana

Abstract


Bacterial colonies infection is one of the causes of bloodstream disease, and it can be a fatality. Therefore, medical diagnoses require fast identification and classification of organisms. Artificial Intelligence with deep learning (DL) can now be developed as a rapid bacterial classification. The research aims to combine deep learning and support vector machines (SVM). The ResNet-101 model of the DL algorithm extracted the image’s features using transfer learning then classified by the SVM classifier. According to the experimental results, this model had 99.61% accuracy, 99.58% recall, 99.58% precision, and 99.97% specificity. The technique presented might enhance clinical decision-making.

Keywords


Bacterial colonies; Deep learning; Transfer Learning; Support Vector Machine

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DOI: http://doi.org/10.11591/ijeecs.v26.i1.pp352-361

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The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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