论文标题
使用卷积神经网络和Canny Edge检测在分段的血细胞中检测疟疾检测
Malaria detection in Segmented Blood Cell using Convolutional Neural Networks and Canny Edge Detection
论文作者
论文摘要
我们应用卷积神经网络来鉴定从薄血液涂片滑动图像中感染的疟疾和未感染的分段细胞之间。我们优化了模型，以发现超过95％的疟疾细胞检测精度。我们还采用巧妙的图像处理来减少培训文件大小，同时保持可比的精度（〜94％）。
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%).
