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Camera Calibration / Augmented Reality/ Stereo Disparity Map/ SIFT/ Training Cifar-10 Classifier Using VGG16
This project demonstrates image classification using a Convolutional Neural Network (CNN) on the CIFAR-10 dataset. The model is trained to classify images into one of 10 classes.
The code does image classification using the CIFAR-10 dataset. Two models, ANN and CNN, are trained on 32x32 color images across 10 classes. Following data preprocessing, the models are constructed and trained. Their classification performance is assessed on test images, highlighting their effectiveness in identifying objects within the dataset.