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All Journal Jurnal Ilmu Komputer dan Informasi Computer Science and Information Technologies
Alfin, Muhammad Reza
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Computer Science & IT Engineering

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Journal : Computer Science and Information Technologies

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Transfer learning: classifying balanced and imbalanced fungus images using inceptionV3 Supriyadi, Muhamad Rodhi; Alfin, Muhammad Reza; Karisma, Aulia Haritsuddin; Maulana, Bayu Rizky; Pinem, Josua Geovani
Computer Science and Information Technologies Vol 5, No 2: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i2.p112-121

Abstract

Identifying the genus of fungi is known to facilitate the discovery of new medicinal compounds. Currently, the isolation and identification process is predominantly conducted in the laboratory using molecular samples. However, mastering this process requires specific skills, making it a challenging task. Apart from that, the rapid and highly accurate identification of fungus microbes remains a persistent challenge. Here, we employ a deep learning technique to classify fungus images for both balanced and imbalanced datasets. This research used transfer learning to classify fungus from the genera Aspergillus, Cladosporium, and Fusarium using InceptionV3 model. Two experiments were run using the balanced dataset and the imbalanced dataset, respectively. Thorough experiments were conducted and model effectiveness was evaluated with standard metrics such as accuracy, precision, recall, and F1 score. Using the trendline of deviation knew the optimum result of the epoch in each experimental model. The evaluation results show that both experiments have good accuracy, precision, recall, and F1 score. A range of epochs in the accuracy and loss trendline curve can be found through the experiment with the balanced, even though the imbalanced dataset experiment could not. However, the validation results are still quite accurate even close to the balanced dataset accuracy.
Co-Authors ASNAWI Dono Wahyuno Dyah Manohara Karisma, Aulia Haritsuddin Maulana, Bayu Rizky Melati Miftakhurohmah Pinem, Josua Geovani Putri Ayu Pramesti, Putri Ayu Rita Noveriza Siti Hardiyanti Supriyadi, Muhamad Rodhi Warman, Riki