Classification of Pneumonia images on mobile devices with Quantized Neural Network

Authors

DOI:

https://doi.org/10.33448/rsd-v9i10.8382

Keywords:

Classification; Images; Quantization; Mobile Devices; Pneumonia.

Abstract

This paper presents an approach for the classification of child chest X-ray images into two classes: pneumonia and normal. We employ Convolutional Neural Networks, from pre-trained networks together with a quantization process, using the platform TensorFlow Lite method. This reduces the processing requirement and computational cost. Results have shown accuracy up to 95.4% and 94.2% for MobileNetV1 and MobileNetV2, respectively. The resulting mobile app also presents a simple and intuitive user interface.

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Published

19/09/2020

How to Cite

SOUSA, J. V. M. .; ALMEIDA, V. R. de .; SARAIVA, A. A. .; SANTOS, D. B. S. .; PIMENTEL, P. M. C.; SOUSA, L. L. de . Classification of Pneumonia images on mobile devices with Quantized Neural Network. Research, Society and Development, [S. l.], v. 9, n. 10, p. e889108382, 2020. DOI: 10.33448/rsd-v9i10.8382. Disponível em: https://www.rsdjournal.org/index.php/rsd/article/view/8382. Acesso em: 28 jun. 2022.

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Section

Engineerings