Malaria detection in Segmented Blood Cell using Convolutional Neural Networks and Canny Edge Detection

• URL: http://arxiv.org/abs/2202.10426v1
• Date: Mon, 21 Feb 2022 18:34:35 GMT
• Title: Malaria detection in Segmented Blood Cell using Convolutional Neural Networks and Canny Edge Detection
• Authors: Tahsinur Rahman Talukdar, Mohammad Jaber Hossain, Tahmid H. Talukdar
• Abstract summary: We optimize our model to find over 95% accuracy in malaria cell detection. We also apply Canny image processing to reduce training file size while maintaining comparable accuracy.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: We apply convolutional neural networks to identify between malaria infected and non-infected segmented cells from the thin blood smear slide images. We optimize our model to find over 95% accuracy in malaria cell detection. We also apply Canny image processing to reduce training file size while maintaining comparable accuracy (~ 94%).

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