White Blood Cell Classification is a deep learning project built with Python, TensorFlow, and Keras that classifies five types of WBCs from microscopic images using a CNN model. With advanced image preprocessing, data augmentation, and a robust architecture, it achieves up to 95% test accuracy.
artificial-intelligence convolutional-neural-networks biomedical-image-processing artifical-neural-network tensorflow-keras cnn-image-classification deep-learning-project deep-learning-healthcare white-blood-cell-classification microscopic-image-classification kaggle-dataset-project
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Updated
Oct 16, 2025 - Jupyter Notebook