APPLICATION OF CONVOLUTIONAL NEURAL NETWORKS FOR DETECTION OF PNEUMONIA DISEASE IN PATIENTS
DOI:
https://doi.org/10.24867/26BE05StojanovKeywords:
Convolutional neural networks, image processing and analysis, image classificationAbstract
This paper shows the application of convolutional neural networks in detection of pneumonia in patients. Basics of neural networks and how they work are explained. The process and technologies used in image processing and analysis are shown in detail in this paper. The dataset, publicly available, consists of chest x-rays and was used in the research. The paper presents two arcitectures of convolutional neural networks and their classification results are compared with the results of other research.
References
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[2] Chouhan, Vikash, et al. "A novel transfer learning based approach for pneumonia detection in chest X-ray images." Applied Sciences 10.2 (2020): 559.
[3] Sze, Vivienne, et al. "Efficient processing of deep neural networks: A tutorial and survey." Proceedings of the IEEE 105.12 (2017): 2295-2329.
[4] Sang, Jonghee, Soomyung Park, and Junwoo Lee. "Convolutional recurrent neural networks for urban sound classification using raw waveforms." 2018 26th European Signal Processing Conference (EUSIPCO). IEEE, 2018.
[5] Hijazi, Samer, Rishi Kumar, and Chris Rowen. "Using convolutional neural networks for image recognition." Cadence Design Systems Inc.: San Jose, CA, USA (2015): 1-12.
[6] Goutte, Cyril, and Eric Gaussier. "A probabilistic interpretation of precision, recall and F-score, with implication for evaluation." European conference on information retrieval. Springer, Berlin, Heidelberg, 2005.
[7] Alzubaidi, Laith, et al. "Review of deep learning: Concepts, CNN architectures, challenges, applications, future directions." Journal of big Data 8 (2021): 1-74
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Published
2024-03-02
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Section
Electrotechnical and Computer Engineering
