Bit Masking Accelerated Optimization Dataset

This dataset selects the CIFAR-10 small-scale general object recognition dataset, which contains a total of 60,000 RGB color images with a size of 32×32, belonging to 10 categories. The dataset is divided into a training set of 40,000 images, a testing set of 10,000 images, and a validation set of 10,000 images. The images in the dataset are processed with bit masking, and the image classification results are compared with those of the original dataset, providing an experimental basis for the study of how bit masking improves the accuracy and speed of the algorithm.