… classification, we introduce the architecture of classic vision Transformers and compare it with convolutional neuralnet… , we discuss Transformer-basedmodels and their roles on feature …
… models include convolutional neuralnetworks (CNN), deep … This step is repeated through multiple neural layers. Then, … layer, where predictions and masks are made, leading to the …
… models in natural language processing in recent years, researchers have explored the application of Transformer-basedmodels … for the smooth L1 loss used in the Mask R-CNN paper. …
葛轶洲, 许翔, 杨锁荣, 周青… - Journal of Frontiers of …, 2021 - search.ebscohost.com
… 图3(d)的效果, 被称为频率掩蔽(frequency masking).实验证明该方 … diction of power systems based on deepresidualnetwork and data … learning for automaticmodulationclassification[J]. …
… bias, the masks for the glass potential were automatically chosen to be all glass area at least 3 fibril diameters away from the fibril masks edge and the fibril potential mask was a stripe …
温俊芳, 宋庆增 - Computer Science and Application, 2022 - hanspub.org
… of classification. In this paper, we carried out user guidance baseddeep learning classification … We select six popular deep learning models on three real datasets for the evaluation. The …