Microscopic blood cell classification using deep learning and image processing techniques.
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Updated
May 28, 2026 - Jupyter Notebook
Microscopic blood cell classification using deep learning and image processing techniques.
This project implements a CNN to classify WBCs from microscopic images into 8 different classes. The model is trained using stratified 5-fold CV and a weighted random sampler. It supports single/batch inference. All modules conform to an interface file-based grading/evaluation system.
Academic deep learning project comparing CNNs, Batch Normalization and ResNet18 transfer learning for blood cell image classification.
Multi-class blood cell classification using CNNs, transfer learning, and data augmentation, evaluated on Codabench.
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