There are 2 repositories under blood-cells topic.
Machine learning approach of automatic identification and counting of blood cells (RBC, WBC, and Platelet) with KNN and IOU based verification.
The complete blood count (CBC) dataset contains a total of 360 blood smear images of red blood cells (RBCs), white blood cells (WBCs), and Platelets with annotations.
Large-Scale Multi-Class Image-Based Cell Classification with Deep Learning
Using deep learning and CNN model
The purpose of our project is to develop a system that can automatically detect cancer from the blood cell images. This system uses a convolution network that inputs a blood cell images and outputs whether the cell is infected with cancer or not.
This is a complete service of blood cell image classification using a Convolutional Neural Network, with an FastAPI backend and ReactJS web app
Using TensorFlow Object Detection API to detect blood cells
My Blood Cell Report is a native iOS mobile application developed using a Machine learning text classification model trained in coreML (apple developer framework) to measure the impact of diseases on blood cells using symptoms as input (provided in texts in the application).
Detecting Blood Cells in Blood Images using a patch-based Neural Network approach
Working demo can be found at