AI Brain Tumor Detector
Steven
Collaboration & Role
I worked in a team of three to research and compare CNN architectures for MRI brain tumor classification.
I was responsible for the model design, training, optimization, data augmentation , and performance evaluation in TensorFlow.
Model Engineering
I built a 4 class MRI classifier (Glioma, Meningioma, Pituitary, No Tumor).
I implemented a custom CNN from scratch and a transfer- earning model using pretrained VGG16, then compared them.
I standardized input by resizing scans, normalizing pixels, and designing reproducible supervised data loaders.
Performance & Optimization
I optimized training iteration speed, achieving 16.5X faster training cycles by optimizing data loading.
I optimized data augmentation to reduce overfitting and handle class imbalance.
I implemented learning rate scheduling and early stopping to cut wasted compute and improve convergence.
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Posted Jan 6, 2026
Developed and optimized two convolutional neural networks for MRI brain tumor classification using TensorFlow.
