image classification model

implemented an optimized convolutional neural network based on the vgg16 architecture for image classification on cifar-10, achieving 92% accuracy while maintaining strong performance.

reduced the model size to 4mb for efficient deployment on resource-constrained systems and built an image preprocessing pipeline to ensure consistent input quality.