- This project deals with the detection and classification of White Blood cells(WBCs) using deep learning object detection architecture called YOLOv3.
- The model performs the task by detecting WBCs from blood images using YOLOv3 and a pretrained Convolutional Neural Network(CNN) called Darknet53 as its feature extractor.
- The detection and classification of WBCs can aid in detection and diagnosis of Leukaemia
- The model is built using Pytorch API
ashraja941/Wbc-Classification-using-Yolov3
Classification of White blood cells into its 5 types using the pytorch implementation of yolov3
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