Computer Science
2 years ago

Deep learning outperforms traditional methods in classifying blood cell images with 95% accuracy.

2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)
Deep Convolution Neural Network for RBC Images
Rajaram Jatothu, Arikatla Sireesha, R. Ganesh Kumar, Kapil Joshi

Paper Summary

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The goal of the study was to improve the accuracy of classifying pictures of red blood cells (RBC) by using a Deep Convolutional Neural Network instead of a regular one. The researchers used a dataset of 790 RBC images and found that the Deep Convolutional Neural Network had a higher accuracy (95.2%) and lower error rate (85.8%) compared to the regular Convolutional Neural Network. This means that the Deep Convolutional Neural Network is better at identifying and classifying blood cell images.