YOLO-V3 based real-time drone detection algorithm
Mar 26, 2022
DOI:
Published in: Multimedia Tools and Applications
Drones are currently being used in a wide range of useful tasks that are too dangerous and/or expensive to be performed by humans. However, this is increasingly developing security breaching issues due to the possibility of misuse of unmanned aircraft in illegal activities such as drug smuggling, terrorism, etc. Thus, the detection and tracking of drones are becoming crucial topics. Unfortunately, due to the drone’s small size, its detection methods are generally unreliable: high false alarm rate, low accuracy rate, and low detection speed are well-known aspects of this detection. The new emerging real-time algorithm based on the improved “You Only Look Once” (YOLO-V3) algorithm is proposed here for drone detection. This newly designed algorithm comprises multiple phases and has shown the potential to outperform the traditional detection approaches. The proposed algorithm enhances the performance of YOLO-V3 by designing and building a CNN to solve the problem of a large number of YOLO-V3 parameters, using densely connected modules to enhance the interlayer connection of CNNs and further strengthen the connection between dense neural network blocks, and finally improving the YOLO-V3 multiple-scale detection by expanding the three-scale to four-scale detection to increase the accuracy of detecting small objects like drones. The evaluation results of our algorithm obtain 96% average precision and 95.60% accuracy.
Other Researches
Modified YOLOv8x model for coronary stenosis detection and troponin risk stratification
Detection of coronary artery stenosis and risk stratification of troponin play a pivotal role in offering early diagnosis and treatment of cardiovascular diseases. In this paper, an improved deep learning framework that allows using both spatial and...
PUF-Enabled Key-Exchange Protocol for Vehicular Ad-Hoc Networks
The Internet of Vehicles (IoV) enables data exchange among individuals, cloud resources, road infrastructures, and vehicles, interconnected through Vehicular Ad Hoc Networks (VANETs). VANETs comprise vehicles with Onboard Units (OBUs), Roadside Unit...
LSOARP: A Link Stability and Obstacle-Aware Routing Protocol for UAV Networks
As using Unmanned Aerial Vehicles (UAVs) continues to grow across military, environmental, and public safety sectors, we are seeing a fast development of Flying Ad Hoc Networks (FANETs). Despite this progress, creating reliable routing protocols for...
Generalizing location-centric variations to enhance contactless human activity recognition
Contactless Human Activity Recognition (HAR) has played a critical role in smart healthcare and elderly care homes to monitor patient behavior and detect falls or abnormal activities in real time. The effectiveness of non-invasive HAR is often hinde...
Filtered orthogonal frequency division multiplexing (F-OFDM), employed in visible light communication (VLC) systems, has been considered a promising technique for overcoming OFDM’s large out-of-band emissions and thus reducing bandwidth efficiency. ...
Malware Detection with Subspace Learning-based One-Class Classification
Detecting malware is crucial for ensuring the security of computer systems. Traditional machine learning models face challenges in effectively detecting malware, mainly due to the class imbalance problem, where the number of malware samples is signi...
The filtered-orthogonal frequency division multiplexing (F-OFDM) scheme has gained attention as a promising solution in the field of visible light communication (VLC) systems. One crucial aspect in VLC is the conversion of the complex F-OFDM signal ...
Wildfires are common disasters that have long-lasting climate effects and serious ecological, social, and economic effects due to climate change. Since Earth observation (EO) satellites were launched into space, remote sensing (RS) has become a more...
Impact of portable executable header features on malware detection accuracy
One aspect of cybersecurity incorporates the study of Portable Executable (PE) file maleficence. Artificial Intelligence (AI) can be employed in such studies, since AI has the ability to discriminate benign from malicious files. In this study, an ex...
Novel partial overlapped gaussian pulse multi-access system aided by data analysis
Orthogonal frequency-division multi-access (OFDMA) systems have limited flexibility to improve efficiency due to their dependency on subcarrier orthogonality. As a result of this restriction, attention has shifted to a new multi-access communication...