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Multi-Drone based Single Object Tracking with Agent Sharing Network [article]

Pengfei Zhu, Jiayu Zheng, Dawei Du, Longyin Wen, Yiming Sun, Qinghua Hu
2020 arXiv   pre-print
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]

Yuanqiang Cai, Dawei Du, Libo Zhang, Longyin Wen, Weiqiang Wang, Yanjun Wu, Siwei Lyu
2019 arXiv   pre-print
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]

Siqi Gu, Zhichao Lian
2022 arXiv   pre-print
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

Xiaolong Chen, Hai Zhang, Jie Song, Jian Guan, Jiefang Li, Ziwen He
2022 Remote Sensing  
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

Muhammad Asif Khan, Hamid Menouar, Aisha Eldeeb, Adnan Abu-Dayya, Flora D. Salim
2022 IEEE Sensors Journal  
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]

Chen Rui, Guo Youwei, Zheng Huafei, Jiang Hongyu
2021 arXiv   pre-print
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

Dawei Du, Yue Zhang, Zexin Wang, Zhikang Wang, Zichen Song, Ziming Liu, Liefeng Bo, Hailin Shi, Rui Zhu, Aashish Kumar, Aijin Li, Almaz Zinollayev (+91 others)
2019 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)  
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

Parham Nooralishahi, Fernando Lopez, Xavier P. V. Maldague
2022 IEEE Access  
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

Han Sun, Jian Yang, Jiaquan Shen, Dong Liang, Ningzhong Liu, Huiyu Zhou
2020 IEEE Access  
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

Bailin Liu, Huan Luo
2022 Electronics  
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

Wei Huang, Xiaoshu Zhou, Mingchao Dong, Huaiyu Xu
2021 Multimedia tools and applications  
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)  
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]

Hao Xu, Yichen Zhang, Boyu Zhou, Luqi Wang, Xinjie Yao, Guotao Meng, Shaojie Shen
2022 arXiv   pre-print
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

Ali Safa, Tim Verbelen, Ilja Ocket, Andre Bourdoux, Francky Catthoor, Georges Gielen
2021 IEEE Robotics and Automation Letters  
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

Simeon Okechukwu Ajakwe, Vivian Ukamaka Ihekoronye, Dong-Seong Kim, Jae Min Lee
2022 Drones  
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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