Shape vs. Texture Bias in CNNs analysis pipeline

A comprehensive analysis framework to quantify and visualize shape bias versus texture bias in Convolutional Neural Networks (CNNs). This project evaluates how modern CNN architectures (VGG16, ResNet50, AlexNet) make predictions based on shape features versus texture features when processing images with conflicting cues.