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Multi-Drone based Single Object Tracking with Agent Sharing Network
[article]
2020
arXiv
pre-print
Preserved Fulltext
Besides, two evaluation metrics are specially designed for multi-drone single object tracking, i.e. automatic fusion score (AFS) and ideal fusion score (IFS). ...
In this paper, we collect a new Multi-Drone single Object Tracking (MDOT) dataset that consists of 92 groups of video clips with 113,918 high resolution frames taken by two drones and 63 groups of video ...
Based on the OPE, AFS and IFS are proposed for multi-drone tracker. ...
arXiv:2003.06994v1
fatcat:rkj2cogrgnctxakbmyj4iywtay
Guided Attention Network for Object Detection and Counting on Drones
[article]
2019
arXiv
pre-print
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In this paper, we propose a new Guided Attention Network (GANet) to deal with both object detection and counting tasks based on the feature pyramid. ...
Object detection and counting are related but challenging problems, especially for drone based scenes with small objects and cluttered background. ...
Output Predictor Based on multi-scale feature fusion, we predict the scales and locations of objects using both score and location maps (see Figure 1 (c)), which are defined as follows: • The score map ...
arXiv:1909.11307v1
fatcat:ukkt4xm7djap5kwmsrpxbbjofa
A Unified Multi-Task Learning Framework of Real-Time Drone Supervision for Crowd Counting
[article]
2022
arXiv
pre-print
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To improve the accuracy, we propose the Extensive Context Extraction Module (ECEM) that is based on a dense connection architecture to encode multi-receptive-fields contextual information and apply the ...
We also design the Assisted Learning Module (ALM) to fuse the density map feature to the image fusion encoder process for learning the counting features. ...
The classic scale-aware CNN-based models handle the scale variation problem by taking advantage of multi-column or multi-resolution architectures, like [1] . ...
arXiv:2202.03843v1
fatcat:7sxuuc2nfrbtnhapxpqqbahsvq
Micro-Motion Classification of Flying Bird and Rotor Drones via Data Augmentation and Modified Multi-Scale CNN
2022
Remote Sensing
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A multi-scale convolutional neural network (CNN) is employed and modified, which can extract both the global and local information of the target's m-D features and reduce the parameter calculation burden ...
In order to increase the number of effective datasets and enhance m-D features, the data augmentation method is designed by setting the amplitude scope displayed in T-F graph and adopting feature fusion ...
The Modified Multi-Scale CNN Model This paper proposes a target m-D feature classification method based on the modified multi-scale CNN [25] , which uses multi-scale splitting of the hybrid connection ...
doi:10.3390/rs14051107
fatcat:ugatpyaw4rdjtk5o52m2y2q6yi
On the Detection of Unauthorized Drones - Techniques and Future Perspectives: A Review
2022
IEEE Sensors Journal
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Based on the review, we provide key insights on the future drone detection systems. ...
To safeguard critical assets and infrastructure and to protect privacy of people from the illegitimate uses of commercial drones, a drone detection system is inevitable. ...
or multi-class classification (identification of a drone based on the make, model, activity or a unique ID). ...
doi:10.1109/jsen.2022.3171293
fatcat:wmws5gupsjdzhni6o7rj7p4cdu
A Comprehensive Approach for UAV Small Object Detection with Simulation-based Transfer Learning and Adaptive Fusion
[article]
2021
arXiv
pre-print
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Deep learning is widely adopted for UAV object detection whereas researches on this topic are limited by the amount of dataset and small scale of UAV. ...
To tackle these problems, a novel comprehensive approach that combines transfer learning based on simulation data and adaptive fusion is proposed. ...
Based on the above analysis, we try to improve UAV small object detection from both aspects of data augmentation and multi-scale feature learning. ...
arXiv:2109.01800v1
fatcat:sppgyj4sd5fl3lnk6cc75nvnve
VisDrone-DET2019: The Vision Meets Drone Object Detection in Image Challenge Results
2019
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
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on image object detection on drones. ...
The results demonstrate that there still remains a large room for improvement for object detection algorithms on drones. ...
Feature pyramids are used to generate feature maps of different scales. Multi-scale feature fusion technology enhances the features of feature maps at each level. ...
doi:10.1109/iccvw.2019.00030
dblp:conf/iccvw/DuZWWSLBSZKLZAS19
fatcat:3pjllyrjpngvzc352nkjb3jdku
Drone-Enabled Multimodal Platform for Inspection of Industrial Components
2022
IEEE Access
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to address the problem of dissimilarity of feature appearances in different spectrums.This study presents a comprehensive platform for drone-based multimodal inspection of industrial and construction ...
Using a calibration board with geometrically known features to estimate intrinsic and extrinsic parameters and accurately align the images in thermal and visible spectral bands, is one of the main approaches ...
One of the commonly used techniques for multi-modal data fusion is calibration-based registration. ...
doi:10.1109/access.2022.3167393
fatcat:x3aw4ijuzbaardul72elugh2cq
TIB-Net: Drone Detection Network with Tiny Iterative Backbone
2020
IEEE Access
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Although deep convolutional neural network (CNN) has shown powerful performance in object detection in recent years, most existing CNN-based methods cannot balance detection performance and model size ...
INDEX TERMS Drone detection, tiny iterative backbone, TIB-Net, cyclic pathway, spatial attention, drone benchmark dataset. ...
Dong and Zou proposed a drone detection method with online feature classification based on HOG [22] . ...
doi:10.1109/access.2020.3009518
fatcat:4uqxwlgy6jc3xg6phrv2erfwhu
An Improved Yolov5 for Multi-Rotor UAV Detection
2022
Electronics
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Multi-rotor drones have a wide range of applications in practical scenarios; however, the use of multi-rotor drones for illegal acts is also on the rise, in order to improve the recognition accuracy of ...
multi-rotor drones. ...
Target detection algorithms are mainly divided into traditional target detection algorithms based on artificial features and target detection techniques based on deep neural networks [9] . ...
doi:10.3390/electronics11152330
fatcat:jg6gdm3ydnfudatcjslmmwipq4
Multiple objects tracking in the UAV system based on hierarchical deep high-resolution network
2021
Multimedia tools and applications
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AbstractRobust and high-performance visual multi-object tracking is a big challenge in computer vision, especially in a drone scenario. ...
types and scales of targets, and extract more effective and comprehensive features during online learning. ...
Acknowledgments This work is supported by the Scale Test Verification Assessment and Demonstration Application for SEANET Program of the Chinese Academy of Sciences. Grant No. is XDC02070800. ...
doi:10.1007/s11042-020-10427-1
fatcat:j4ny2wnemrbihnfpdcuvqaisje
VCIP 2020 Index
2020
2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)
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localization
T
S
Sang, Liu
Deep Convolutional Neural Network Based on
Multi-Scale Feature Extraction for Image
Denoising
Santos, João M. ...
ANOMALY DETECTION FOR FACE PRESENTATION ATTACK DETECTION WITH MULTI-CHANNEL IMAGES Zhang, Yuhang Video Super Resolution Using Temporal Encoding ConvLSTM and Multi-Stage Fusion Zhang, Yun Sparse Representation-Based ...
doi:10.1109/vcip49819.2020.9301896
fatcat:bdh7cuvstzgrbaztnahjdp5s5y
Omni-swarm: A Decentralized Omnidirectional Visual-Inertial-UWB State Estimation System for Aerial Swarms
[article]
2022
arXiv
pre-print
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It consists of stereo wide-FoV cameras and ultra-wideband sensors, visual-inertial odometry, multi-drone map-based localization, and visual drone tracking algorithms. ...
The measurements from the front-end are fused with graph-based optimization in the back-end. ...
Multi-drone Map-based Localization Module Similar to the approach used in VINS-Fisheye, we also perform visual object detection on distortion-free images. ...
arXiv:2103.04131v4
fatcat:ynivmhsg5zc6vptov6me5oplp4
Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach
2021
IEEE Robotics and Automation Letters
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Currently however, people detection systems used on drones are solely based on standard cameras besides an emerging number of works discussing the fusion of imaging and event-based cameras. ...
In order to enable the fusion of radars with both event-based and standard cameras, we present KUL-UAVSAFE, a first-of-its-kind dataset for the study of safety-critical people detection by drones. ...
Ablation studies 1) Cross-fusion vs. early-fusion: In Section IV-B, we motivated our use of a cross-fusion strategy in order to enable the network to learn at which feature scales fusion should happen ...
doi:10.1109/lra.2021.3125450
fatcat:z27e6jqrlnaedoezds4exewxey
DRONET: Multi-Tasking Framework for Real-Time Industrial Facility Aerial Surveillance and Safety
2022
Drones
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In this work, a vision-based multi-tasking anti-drone framework is proposed to detect drones, identifies the airborne objects, determines its harmful status through perceived threat analysis, and checks ...
The emergence of non-military use of drones especially for logistics comes with the challenge of redefining the anti-drone approach in determining a drone's harmful status in the airspace based on certain ...
These results validate the superiority of DRONET's performance as a reliable and efficient model for adaptive multi-scale anti-drone system design suitable for real time visual multi-drone detection and ...
doi:10.3390/drones6020046
fatcat:pgdb43fjs5hh7ch6pdtbcxabjq
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