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Cancer Detection Dataset & Preprocessing Guide by stationfunstop is a document available to read on EtoBox.

The Cancer Detection Project involves a dataset of medical images resized to 224x224 pixels, primarily in JPG format, containing five cancer classes with approximately 2,000 to 5,000 images each. Preprocessing techniques included resizing, grayscale conversion, normalization, and noise reduction, while augmentation was applied mainly to underrepresented classes to enhance model performance. The dataset was split into training, validation, and test sets using a 70:15:15 ratio, with stratified splitting to ma

Author

stationfunstop

Language

EN