Pedestrian detection models Accessories in autonomous driving systems heavily rely on deep neural networks (DNNs) to perceive their surroundings.Recent research has unveiled the vulnerability of DNNs to backdoor attacks, in which malicious actors manipulate the system by embedding specific triggers within the training data.In this paper, we propose
The new power system with new energy as the main body gives the low-voltage distribution network (LVDN) a richer connotation, requiring intelligent measurement equipment to have good scalability and collaborative ability.To address these requirements, an optimization configuration model for intelligent measurement multi-core modules considering &#x
BackgroundMaternal over- and undernutrition in pregnancy plays a critical role in fetal brain development and function.The effects of different maternal diet compositions on intrauterine programing of the fetal brain is a lesser-explored area.The goal of this study was to investigate the impact of two chowmaternal diets on fetal brain gene expressi
Disease samples are naturally fewer than healthy samples which introduces bias in the training of machine learning (ML) models.Current study focuses in learning discriminating patterns between cesarean and non-cesarean phenomena based on a dataset consisting of 161 features of total 692 cesarean and 5465 non-cesarean samples which comes as four Not