… propose a deep-learning method based on an improved YOLOv5 object detection model …
application of deep learning, the speed and precision of target detection have gradually …

… Deep learning based methods have the potential to focus on various aspects, including …
This article proposes a data-driven deep learning based model to classify the received raw …

… a deep learning based intelligent method for detecting and identifying radio signals …
automated modulation classification scheme for cognitive radio, which can be used for aeronautical …

… In this paper, we present SDR-Fi, the first reported Wi-Fi software-defined radio (SDR)
receiver for indoor positioning using CSI measurements as features for deep learning (DL) …

… features provide better results in the anomaly detection context with respect to … detector
(CFD). Here, in the proposed framework for spectrum anomaly detection, we compare three deep …

… In this paper, we address the problem of signal denoising: a deep learning model is
applied to radio signals to improve the quality of received signals. By noise, we mean not only …

… the models for the task of detection remains a inhibitory condition for all but … deep learning
from a cost reduction and hybrid perspective — incorporating techniques of transfer learning, …

… UASs uses the distinct sound of propellers to detect UAS … Another existing technique detects
the radio signals that are … a deep learning-based Doppler radar sensor system to detect …

… areas such as cognitive radio (CR). In our paper, we propose a deep learning-based AMC
… In our proposed method, one deep learning technology, Deep Belief Network (DBN), is …

… radio performance gains achieved by applying deep learning. Even though we have studied
different approaches in improving the efficiency of the network, a further study on adapting …