32 天前 - … Secondly, we introduce deep learning as another option to achieve a near-optimal
solution with a much lower complexity. We see how a deep neural network is able to …

32 天前 - … -layer and seven hybrid multilayer deep learning models that combine them. This
study also analyzed the effect of hyperparameters on the learning … of the deep learning model, …

33 天前 - … Image processing techniques are used to examine the products for various physical
attributes like color, texture, quality, and size.We employed deep learning techniques, such …

35 天前 - … In this section, we briefly discusses the physical layer parameters such as RSSI
and CSI followed by FMCW RADAR technology, and other estimated parameters such as AoA …

37 天前 - … machine and deep learning models … layer perceptron (MLP) architecture using a
double gate metal oxide semiconductor field effect transistor (DGMOSFET) model. The physical …

37 天前 - … efficient and robust deep learning model LPLA based on the popular attention
mechanism namely Vision Transformer (ViT) was developed for anti-counterfeiting authentication …

38 天前 - … deep learning-based semantic communication (DLSC) system that simultaneously
incorporates physical-layer … simultaneously incorporates physicallayer semantic encryption …

39 天前 - … We consider a two-layered neural network whose first layer is frozen while the last
layer is … a set of differential equations for the learning dynamics. For any finite ratio of hidden …

39 天前 - … as a potential technology for physical layer authentication of Internet of Things (IoT)
devices. The integration with deep learning has significantly accelerated the advancement …

39 天前 - … a deep learning-based approach for calibrating hardware defects in physical-layer
key … calibration techniques and existing deep-learning models, particularly in environments …