Abstract: In the realm of deep learning, the veracity and integrity of the training data are pivotal for constructing reliable and transparent models. This study introduces the concept of Trustworthy ...

Abstract: This study examines the impact of preprocessing techniques, including stratification, oversampling (SMOTE), undersampling, and PCA, on neural network performance for early detection of type ...

Multiple reports show the data centers used to store, train and operate AI models use significant amounts of energy and water, with a rippling impact on the environment and public health. According to ...