This study proposes robust convolutional neural network (CNN)-based automatic modulation classification (AMC) techniques. Traditional AMCs may be classified into two types: those that rely on ML ...

A new holographic storage technique uses light in three dimensions to dramatically increase how much data can be stored. It encodes information throughout a material using amplitude, phase, and ...

Researchers developed a holographic data storage approach that stores and retrieves information in three dimensions by combining the amplitude, phase and polarization properties of light.Xiaodi Tan, ...

van Vliet and colleagues show a useful correlation between internal states of a convolutional neural network (CNN) trained on visual word stimuli with three specific components of evoked MEG ...

ABSTRACT: In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition ...

The rapid advancement in machine learning techniques and sensing devices over the past decades have opened new possibilities for the detection and tracking of objects, animals, and people. The ...

Abstract: Recent video recognition models utilize Transformer models for long-range spatio-temporal context modeling. Video transformer designs are based on self-attention that can model global ...

In the industrial environment, the positioning of mobile terminals plays an important role in production scheduling. Visible light positioning (VLP) based on a CMOS image sensor has been widely ...

Abstract: Automatic modulation classification (AMC) identifies a received signal’s modulation scheme without prior knowledge of the intercepted signal, which enables significant applications in both ...

Here, we propose an improved YOLOX-Tiny network, named YOLO-Tobacco, for the detection of tobacco brown spot disease under open-field scenarios. Aiming to excavate valuable disease features and ...