conference paper · International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES) · 2022
Deep Convolution Neural Network for RBC Images
Rajaram Jatothu, A. Sireesha, R. Ganesh Kumar, Kapil Kumar Joshi
Cited by 2Abstract and details only
Abstract
The suggested study’s objectives are to develop an unique criterion-based method for classifying RBC pictures and to increase classification accuracy by utilizing Deep Convolutional Neural Networks instead of Conventional CNN Algorithm. Materials and Procedures A dataset-master image dataset of 790 pictures is used to apply Deep Convolutional Neural Network. Convolutional Neural Network and Deep Convolutional Neural Network comparison using deep learning has been suggested and developed to improve classification accuracy of RBC pictures. Using Gpower, the sample size was calculated to be 27 for each group. Results: When compared to Convolutional Neural Network, Deep Convolutional Neural Network had the highest accuracy in classifying blood cell pictures (95.2%) and the lowest mean error (85.8 percent). Between the classifiers, there is a statistically significant difference of p=0.005. The study demonstrates that Deep Convolutional Neural Networks perform more accurately than Conventional Neural Networks while classifying photos of blood cells[1].
Cite this paper
Jatothu, R., Sireesha, A., Kumar, R. G., & Joshi, K. K. (2022). Deep Convolution Neural Network for RBC Images. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), 1–5. https://doi.org/10.1109/icses55317.2022.9914363
Jatothu, Rajaram, et al. “Deep Convolution Neural Network for RBC Images.” International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), 2022, pp. 1–5, https://doi.org/10.1109/icses55317.2022.9914363.
Jatothu, Rajaram, A. Sireesha, R. Ganesh Kumar, and Kapil Kumar Joshi. 2022. “Deep Convolution Neural Network for RBC Images.” International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES): 1–5. https://doi.org/10.1109/icses55317.2022.9914363.
Jatothu, R. et al. (2022) ‘Deep Convolution Neural Network for RBC Images’, International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), pp. 1–5. Available at: https://doi.org/10.1109/icses55317.2022.9914363.
@article{jatothu2022deep,
title = {{Deep Convolution Neural Network for RBC Images}},
author = {Jatothu, Rajaram and Sireesha, A. and Kumar, R. Ganesh and Joshi, Kapil Kumar},
journal = {International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)},
pages = {1--5},
year = {2022},
doi = {10.1109/icses55317.2022.9914363}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.
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