Improving Efficiency of Brain Tumor Classification Models Using Pruning Techniques.

This research highlights the successful application of pruning techniques to reduce the computational complexity of a CNN model for MRI brain tumor classification. The findings suggest that judicious pruning of weights and neurons can lead to a significant improvement in inference time without compromising accuracy.