Statistical Feature

Statistical features, derived from data such as sensor readings, images, or time series, are increasingly used to improve the performance and robustness of machine learning models. Current research focuses on leveraging these features within various architectures, including transformers, convolutional neural networks, and generative adversarial networks, to address challenges like limited data, class imbalance, and out-of-distribution generalization. This work is significant because effective utilization of statistical features enhances model accuracy, efficiency, and adaptability across diverse applications, ranging from manufacturing process optimization and medical image analysis to text generation and anomaly detection.