Image Recognition Using Kernel PCA with Dataset Implementation

Implementation of image recognition through Kernel Principal Component Analysis (KPCA), utilizing 200 test images and 200 training images provided in a compressed archive. The solution includes feature extraction, dimensionality reduction, and classification workflows.