Low-rankness and sparsity are often used to guide the compression of convolutional neural networks (CNNs) separately.Since they capture global and local structure of a matrix respectively, we combine these two complementary properties together to pursue better network compression performance.Most existing low-rank or sparse compression methods comp
Huanglongbing is an economically devastating disease of citrus in Florida and around the world.This study was undertaken to assess two grower-used therapies, heat treatment, and foliar anti-bacterial application.Specifically, read more there was an industry claim that heat treatment improved subsequent systemic uptake of foliar-applied anti-bacteri
Abstract Background Stroke is a significant contributor of worldwide disability and morbidity with substantial economic consequences.Rehabilitation is a vital component of stroke recovery, but inpatient stroke rehabilitation programs can struggle to meet the recommended hours of therapy per day outlined by the Canadian Stroke Best Practices and Ame
To solve the problems of untimely and low accuracy of tunnel project collapse risk prediction, this study proposes a method of multi-source information fusion.The method uses the PSO-SVM model to predict the surrounding rock displacement.With the prediction index as the benchmark, the Cloud Model (CM) is used to calculate the basic probability hyfr