Fashion MNIST

Fashion-MNIST is a benchmark dataset of clothing images used to evaluate and compare various machine learning models, primarily focusing on image classification. Current research explores diverse model architectures, including convolutional neural networks (CNNs), vision transformers (ViTs), and novel approaches like Kolmogorov-Arnold networks (KANs) employing combinations of mathematical functions, as well as quantum computing and hyperdimensional computing methods. This dataset's significance lies in its role as a testing ground for advancing image recognition techniques, with implications for applications such as e-commerce image retrieval and efficient object representation in resource-constrained environments.