Indeed, many different types of UAVs exist with different capabilities responding to different user needs. january/february 2008 The purpose of this column is to give the reader an overview of the large number of existing UAV systems and R&D projects as well as the practical challenges facing ...
Exploring Radar Micro-Doppler Signatures for Recognition of Drone Types drone type classificationmicro-DopplerUAVSIn this study, we examine the use of micro-Doppler signals produced by different blades (i.e., puller and ... J Yan,H Hu,DLD Gong - 《Drones》 被引量: 0发表: 2023年 UAVs and...
Fine classification of urban nighttime lighting is a key prerequisite step for small-scale nighttime urban research. In order to fill the gap of high-resolution urban nighttime light image classification and recognition research, this paper is based on a small rotary-wing UAV platform, ...
In this paper, we first analyze FMCW radar returns from various types of UAVs and non-UAV objects in terms of the micro-Doppler signature (m-DS) pattern. Based on the analysis results, we propose an effective and efficient UAV classification system using FMCW radar echo signals. The proposed...
Unmanned Aerial Vehicles (UAVs), have greatly revolutionized the process of gathering and analyzing data in diverse research domains, providing unmatched adaptability and effectiveness. This paper presents a thorough examination of Unmanned Aerial Vehicle (UAV) datasets, emphasizing their wide range of app...
Machine learning-based test selection for simulation-based testing of self-driving cars software 2023, Empirical Software Engineering Automated Identification and Qualitative Characterization of Safety Concerns Reported in UAV Software Platforms 2023, ACM Transactions on Software Engineering and Methodology ...
Extracting useful features at multiple scales is a crucial task in computer vision. The emergence of deep-learning techniques and the advancements in convolutional neural networks (CNNs) have facilitated effective multiscale feature extraction that resul
a neural network that was a concatenation of the ResNet50 and MobileNet models for overall prediction capability improvement. 5400 olive leaf images were taken from an olive grove using a remote-controlled agricultural unmanned aerial vehicle (UAV) equipped with a camera to create the dataset used...
Show abstract Deep learning with unsupervised data labeling for weed detection in line crops in UAV images 2018, Remote Sensing A review of advanced machine learning methods for the detection of biotic stress in precision crop protection 2015, Precision Agriculture View all citing articles on Scopus1...
ones including DJI GS Pro, PIX4D Capture, DroneDeploy, UGCS, Altizure, Waypoint Master) by simultaneously considering the area of interest (i.e., boundary shape, terrain), the required ground sample distance and the characteristics (e.g., image resolution, field of view) of UAV cameras [86...