Adversarial machine learning is a recent area of study that explores both adversarial attack strategy and detection systems of adversarial attacks, which are inputs specially crafted to outwit the classification of detection systems or disrupt the training process of detection systems.In this research, we performed two adversarial attack scenarios,
Abstract Background There is growing evidence of nervous system involvement and related complaints in children with coronavirus disease 2019 (COVID-19).However, it seems that attempts to track of the virus in the nervous system have so far been unsuccessful.Case presentation Here we describe two pediatric cases of severe COVID-19 who had positive c
Rugby-related renal trauma is rare and identification of a young patient with renal trauma secondary to sports who requires observation versus further radiological evaluation in the emergency department (ED) poses a diagnostic challenge.We report a case of a 16-year-old girl who presented to the ED with abdominal pain after being tackled during a g
PurposePancreatic cancer is characterized by a grim prognosis and is regarded as one of the most formidable malignancies.Among the genes exhibiting high expression in different tumor tissues, ITGA2 stands out as a promising candidate for cancer therapy.The promotion of cancer in pancreatic cancer is not effective.The objective of this study is to a
The detection of the impurity rate in machine-picked seed cotton is crucial for precision agriculture.This study proposes a novel Cotton-YOLO-Seg cotton-impurity instance segmentation algorithm based on the you Treat Cartons and Boxes only look once version 8 small segmentation model (Yolov8s-Seg).The algorithm achieves precise pixel-level segmenta