Exploiting Convolutional Neural Network for Automatic Fungus Detection in Microscope Images

The fungus detection system is a part of biomedical technology which is used to classify fungus species for investigate mycoses. Recently, fungus are mostly effect to human health, food, and plant. The previous works were used computer vision techniques to detect the fungus, however, the previous researches are shown that the detection quality were depended on the image processing algorithm. The deep learning which one of the artificial intelligent method, is now applied to biomedical technology. This article presents the exploiting convolutional neural network (C-NN) for automatic fungus detection in microscope images. This experiment focuses on chaetomium and aspergillus fungus which exists in the air, food and human body using convolutional neural network. The results shown that adjusting technique in C-NN can provide results with an achieved 98.03% accuracy.