Neuro-inspired olfactory system: modeling complex neural circuits for efficient odor classification

Xinran Ge; Huisheng Zhang; Jia Yan

doi:10.1117/12.3011500

7 December 2023 Neuro-inspired olfactory system: modeling complex neural circuits for efficient odor classification

Xinran Ge, Huisheng Zhang, Jia Yan

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294138 (2023) https://doi.org/10.1117/12.3011500
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

Electronic nose (E-nose) technology, inspired by the biological olfactory system, has exhibited substantial promise across diverse applications due to its effective odor detection and identification capabilities. This paper presents a novel approach that leverages a bioinspired olfactory bulb model for processing data within E-nose systems. In this study, the complex neural circuits within the olfactory bulb were simulated using a bioinspired model. This method directly harnesses the inherent feature extraction capabilities of the olfactory bulb model, eliminating redundant steps and thereby enhancing classification accuracy. To evaluate the performance of this approach, ten types of toxic gases were classified using Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Linear Discriminant Analysis (LDA) classifiers. The proposed bioinspired olfactory bulb model was compared to traditional data preprocessing methods. Experimental results clearly demonstrate that the bioinspired olfactory bulb model significantly improves classification accuracy compared to traditional methods.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinran Ge, Huisheng Zhang, and Jia Yan "Neuro-inspired olfactory system: modeling complex neural circuits for efficient odor classification", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294138 (7 December 2023); https://doi.org/10.1117/12.3011500

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