In this paper, we consider a heterogeneous repository of drone-enabled a...
5G made a significant jump in cellular network security by offering enha...
Unmanned aerial vehicles (UAVs) have become extremely popular for both
m...
This paper investigates an interference-aware joint path planning and po...
As emerging networks such as Open Radio Access Networks (O-RAN) and 5G
c...
In the medical field, current ECG signal analysis approaches rely on
sup...
Indoor localization has gained significant attention in recent years due...
Passive space-borne radiometers operating in the 1400-1427 MHz protected...
Deep learning image processing models have had remarkable success in rec...
Facial expressions convey massive information and play a crucial role in...
The next-generation wireless networks are required to satisfy a variety ...
Cooperative ad-hoc UAV networks have been turning into the primary solut...
Electrocardiogram (ECG) datasets tend to be highly imbalanced due to the...
Unmanned aerial vehicles (UAVs) have been increasingly used in a wide ar...
Cooperative ad hoc unmanned aerial vehicle (UAV) networks need essential...
Unmanned Aerial Vehicles (UAVs), as a recently emerging technology, enab...
Current networking protocols deem inefficient in accommodating the two k...
The electrocardiogram (ECG) signal is the most widely used non-invasive ...
This study presents a new viewpoint on ECG signal analysis by applying a...
Cooperative UAV networks are becoming increasingly popular in military a...
Wildfires are one of the costliest and deadliest natural disasters in th...
This paper introduces Multi-Level feature learning alongside the Embeddi...
Unmanned aerial vehicles (UAVs) have been increasingly utilized in vario...
Electrocardiogram (ECG) signal is the most commonly used non-invasive to...
This paper introduces a novel perspective about error in machine learnin...
This paper proposes inverse feature learning as a novel supervised featu...
Atrial fibrillation (AF) is one of the most prevalent cardiac arrhythmia...
In a world with data that change rapidly and abruptly, it is important t...
This paper studies the problem of spectrum shortage in an unmanned aeria...
This study proposes a deep learning model that effectively suppresses th...
The vast areas of applications for IoTs in future smart cities, industri...
This paper provides a proof of concept for using SRAM based Physically
U...
The high rate of false alarms in intensive care units (ICUs) is one of t...
In this paper, we study the problem of spectrum scarcity in a network of...
In this paper, we propose a drone-based wildfire monitoring system for r...
Electroencephalogram (EEG) is a common base signal used to monitor brain...
Reinforcement learning (RL) techniques, while often powerful, can suffer...
In this paper, we develop a distributed mechanism for spectrum sharing a...
In this paper, a general cognitive radio system consisting of a set of u...
In recent years, using a network of autonomous and cooperative unmanned
...
Unmanned aerial vehicles (UAVs), commonly known as drones, are becoming
...
Some of the main challenges towards utilizing conventional cryptographic...
High false alarm rate in intensive care units (ICUs) has been identified...
The problem of decentralized multiple Point of Interests (PoIs) detectio...
The problem of cooperative spectrum leasing to unlicensed Internet of Th...
The exponentially increasing number of ubiquitous wireless devices conne...
The problem of adversary target detection and the subsequent task comple...
False alarm is one of the main concerns in intensive care units and can
...