Identification of Microorganism Colony Odor Signature using InceptionTime

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Microorganisms that cause infectious diseases are defined as pathogens, as they multiply and cause tissue damage. All microorganisms isolated in culture from a location on the body should be considered potential pathogens. The infectious processes demonstrate physiological responses to the multiplication invasion of the aggressor microorganism. The disease’s development is influenced by the patient’s general health, defense mechanisms, and previous contact with the offending agent. When an infectious disease is suspected, cultures should be performed. This article uses an electronic nose to collect and analyze volatile organic compounds VOCs expelled by colonies of microorganisms. We propose signature identification of these colony odors from microorganisms using InceptionTime. The InceptionTime model is a set of models of the deep convolutional neural network, inspired by the Inception-v4 architecture. The results were excellent, with an average accuracy in the test set above 98%. The aim of our research is to propose a faster, cheaper and more accurate method of detecting these pathogens and the encouraging results of this stage encourage further research.

https://doi.org/10.1109/SMC52423.2021.9658669

David Macêdo, PhD
David Macêdo, PhD
Deep Learning

My interests include everything related to deep learning.

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