Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: International Conference on Neuroinformatics, 2021
Год издания: 2022
Идентификатор DOI: 10.1007/978-3-030-91581-0_27
Ключевые слова: convolutional neural network, hyperparameter, optimization, ziehl-neelsen
Аннотация: Globally, tuberculosis (TB) is the leading infectious killer in the world before pandemia. This paper presents the result of optimizing convolutional neural network architecture for the detection of acid-fast stained TB bacillus. The experimental set contains the segmentation results of microscopy images of the patients sputum staiПоказать полностьюned by the Ziehl–Neelsen method. The authors constructed an experimental algorithm for optimizing the original convolutional neural network model, including optimizing the model dimension, data augmentation, adjusting the model parameters, and improving regularization. The authors built few models of convolutional neural networks (CNN) models to recognize TB bacillus, which showed the maximum value of metrics in the experiment. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Журнал: Studies in Computational Intelligence
Выпуск журнала: Vol. 1008 SCI
Номера страниц: 204-209
ISSN журнала: 1860949X
Издатель: Springer Science and Business Media Deutschland GmbH