Automatic Identification and Counting of Blood Cells
Impact of KNN and IOU
In some cases, our model predicts the same platelet twice. To solve this problem we propose k-nearest neighbor (KNN) and intersection over union (IOU) based verification system where we find the nearest platelet of a platelet and calculate their overlap. We are allowing only 10% of overlap between two platelets. If the overlap is more than that then it will be a spurious prediction and we will ignore the prediction.
Prediction on High-Resolution Image (HRI)
We have used our model to detect and count blood cells from high-resolution blood cell smear images. These test images are of the size of ```3872 x 2592``` way higher than the size of our trained images of ```640 x 480```. So, to match the cell size of our trained images we divide those images into grid cells and run prediction in each grid cell and then combine all the prediction results.
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