Article
Geochemistry & Geophysics
Zhonghua Hong, Fan Yang, Haiyan Pan, Ruyan Zhou, Yun Zhang, Yanling Han, Jing Wang, Shuhu Yang, Peng Chen, Xiaohua Tong, Jun Liu
Summary: This study proposes an improved U-Net network model to enhance the segmentation of road cracks in UAV images and verifies its superiority in crack prediction, providing an effective solution for highway infrastructure monitoring and maintenance.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Yue Xi, Wenjing Jia, Qiguang Miao, Xiangzeng Liu, Xiaochen Fan, Hanhui Li
Summary: In this paper, we propose a Fine-grained Target Focusing Network (FiFoNet) that effectively selects multi-scale features, blocks background interference, and enhances the representation of small objects. Furthermore, a Global-Local Context Collector (GLCC) is introduced to extract global and local contextual information for improving low-quality representations. Experimental results demonstrate the superior performance of FiFoNet in object detection for UAV images.
Review
Engineering, Electrical & Electronic
Yuqi Han, Huaping Liu, Yufeng Wang, Chunlei Liu
Summary: Unmanned aerial vehicles have been widely used in military and civilian fields due to their flexibility and efficiency. The vision system, as an essential component of UAVs, has gained significant attention in recent years for various applications. This review focuses on the automatic understanding of visual data collected from UAVs and provides an overview of techniques and developments in object detection, tracking, and semantic segmentation. The challenges and future directions in UAV vision are also highlighted.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Computer Science, Artificial Intelligence
Xiaowei Xu, Xinyi Zhang, Bei Yu, Xiaobo Sharon Hu, Christopher Rowen, Jingtong Hu, Yiyu Shi
Summary: The 55th Design Automation Conference (DAC) held its first System Design Contest (SDC) in 2018, featuring a low power object detection challenge. DAC-SDC'18 attracted more than 110 entries from 12 countries. This paper presents in detail the dataset and evaluation procedure, as well as future improvement directions.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2021)
Article
Computer Science, Information Systems
Naeem Ayoub, Peter Schneider-Kamp
Summary: The use of deep learning-based autonomous drone vision systems shows promising results in detecting faults in power line components, providing an effective solution for real-time on-board power line inspection. Various single-board devices were utilized for experimental evaluation in running deep learning models.
Article
Engineering, Electrical & Electronic
Ang Li, Shouxiang Ni, Yanan Chen, Jianxin Chen, Xin Wei, Liang Zhou, Mohsen Guizani
Summary: This paper proposes a cross-modal knowledge distillation (CKD) enabled object detection paradigm for UAV-based target detection. It achieves comparable detection performance with multi-modal techniques while requiring less computational resources.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Hardware & Architecture
Peng Liu, Han He, Tingting Fu, Huijuan Lu, Abdulhameed Alelaiwi, Md Wasif Islam Wasi
Summary: The use of UAVs is common and they often offload tasks to edge servers for cost-saving. This paper proposes an optimized task offloading strategy using reinforcement learning algorithm, which shows better convergence and performance in practical application scenarios.
Article
Engineering, Electrical & Electronic
Yong Xu, Hongtao Yan, Yue Ma, Pengyu Guo
Summary: The proposed graph-based horizon line detection technique improves image segmentation, identifies the sky-component, extracts the horizon line, computes roll and pitch angles, and provides unbiased attitude angles with error variance of about 2(o), demonstrating validity and robustness.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Yunzuo Zhang, Cunyu Wu, Wei Guo, Tian Zhang, Wei Li
Summary: With the rapid development of the UAV industry, UAV image object detection technology has become a hotspot. This method introduces CFANet, an efficient object detection network for UAV images, which can quickly and effectively detect and accurately classify objects. Experimental results show that the proposed method can achieve significant performance based on ensuring real-time detection compared with other advanced detectors.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Computer Science, Information Systems
Xiaoheng Deng, Jun Li, Peiyuan Guan, Lan Zhang
Summary: This article develops an energy-efficient UAV-aided target tracking system by offloading video processing tasks from UAV to edge nodes. The proposed algorithm achieves higher energy efficiency and lower latency in UAV-aided target tracking compared to existing methods.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Civil
Liang Zhao, Kaiqi Yang, Zhiyuan Tan, Xianwei Li, Suraj Sharma, Zhi Liu
Summary: Vehicular computation offloading is a well-received strategy to execute tasks of legacy vehicles, with the use of mobile edge computing shortening response time but facing challenges in communication quality assurance. UAVs provide a means of establishing communication links and SDN showcases advances in data collection and management. The UVCO algorithm allows UAVs to assist in task forwarding and decision-making, ultimately minimizing the Average System Cost (ASC).
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Sourajit Maity, Avirup Bhattacharyya, Pawan Kumar Singh, Munish Kumar, Ram Sarkar
Summary: This article introduces various methods used for AVD and classification over the past 10 years, compares different methods, discusses their pros and cons, and proposes future research directions towards AVD.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2022)
Article
Computer Science, Hardware & Architecture
Qiang Tang, Lixin Liu, Caiyan Jin, Jin Wang, Zhuofan Liao, Yuansheng Luo
Summary: This paper investigates a mobile edge computing system aided by multiple access points and a UAV. By dividing the computing tasks of IoTDs and jointly optimizing task allocation, power distribution, and UAV trajectory, the goal is to minimize the consumption of communication, calculation, and flight over a finite UAV mission duration. By decomposing the problem and iteratively solving sub-problems through specific methods, the proposed approach outperforms other comparison baselines.
Article
Mathematics
Lyuchao Liao, Linsen Luo, Jinya Su, Zhu Xiao, Fumin Zou, Yuyuan Lin
Summary: This article introduces an Eagle-YOLO detection model based on the characteristics of eagle eyes to address the challenges of object detection in UAV aerial photography images. The model integrates the Large Kernel Attention Module and introduces a large-sized feature map with rich information, and adopts a weighted Bi-FPN network and Eagle-IoU loss to improve the performance of object detection in UAV aerial image scenes.
Article
Environmental Sciences
Kirill Korznikov, Dmitriy Kislov, Tatyana Petrenko, Violetta Dzizyurova, Jiri Dolezal, Pavel Krestov, Jan Altman
Summary: This study compares three neural networks for tree crown recognition using drone-borne imagery and highlights the strengths and limitations of each method. The results provide important insights for selecting appropriate tree recognition methods.
Article
Geography, Physical
Diogo Duarte, Francesco Nex, Norman Kerle, George Vosselman
GISCIENCE & REMOTE SENSING
(2020)
Article
Environmental Sciences
Sofia Tilon, Francesco Nex, Norman Kerle, George Vosselman
Article
Computer Science, Artificial Intelligence
Simone Borsci, Ville V. Lehtola, Francesco Nex, Michael Ying Yang, Ellen-Wien Augustijn, Leila Bagheriye, Christoph Brune, Ourania Kounadi, Jamy Li, Joao Moreira, Joanne Van der Nagel, Bernard Veldkamp, Duc Le, Mingshu Wang, Fons Wijnhoven, Jelmer M. Wolterink, Raul Zurita-Milla
Summary: The article reviews the EU Commission's whitepaper on Artificial Intelligence and highlights potential conflicts with current societal, technical, and methodological constraints. The lack of a coherent EU vision and methods to support sustainable AI diffusion are identified as main obstacles. The article recommends complementary rules and compensatory mechanisms to avoid market fragmentation, as well as research to address technical and methodological open questions for the sustainable development of human-AI co-action.
Article
Environmental Sciences
Ning Zhang, Francesco Nex, George Vosselman, Norman Kerle
Summary: This research focuses on using deep learning to detect victims in disaster debris, proposes a method to generate harmonious composite images for training, and significantly improves detection accuracy.
Article
Environmental Sciences
Sofia Tilon, Francesco Nex, George Vosselman, Irene Sevilla de la Llave, Norman Kerle
Summary: This paper introduces a versatile UAV system that can carry out multiple road infrastructure monitoring tasks simultaneously in real-time. The system design considers computational strain and latency, and it is deployed on a unique typology of UAV. It includes important modules such as vehicle detection, scene segmentation, and 3D scene reconstruction, and has a good performance.
Article
Remote Sensing
Bashar Alsadik, Fabio Remondino, Francesco Nex
Summary: This paper investigates a multi-view camera system integrated with a multi-beam LiDAR to build an efficient UAV hybrid system. Two types of cameras, MAPIR Survey and SenseFly SODA, integrated with a multi-beam digital Ouster OS1-32 LiDAR sensor, are proposed and examined. The results show that with appropriate conditions, high-density facade coverage can be achieved.
Article
Remote Sensing
Samer Karam, Francesco Nex, Bhanu Teja Chidura, Norman Kerle
Summary: This article presents a low-cost SLAM-based drone for creating exploration maps of building interiors. The experimental results indicate that the system is capable of creating quality exploration maps of small indoor spaces and handling the loop-closure problem.
Proceedings Paper
Geography, Physical
S. Karam, F. Nex, O. Karlsson, J. Rydell, E. Bilock, M. Tulldahl, M. Holmberg, N. Kerle
Summary: This paper presents the operations and mapping techniques of two drones used for mapping indoor spaces. Both the Crazyflie and MAX drones are capable of mapping cluttered indoor environments and providing sufficient point clouds for quick exploration. The results show that the LIDAR scanner-based system can handle larger office environments with minimal drift, while the Crazyflie drone performs well given its limited sensor configuration.
XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION I
(2022)
Proceedings Paper
Geography, Physical
Karen K. Mwangangil, P. O. Mc'okeyo, S. J. Oude Elberink, F. Nex
Summary: This research explores the potential of using UAV image data for 3D buildings reconstruction, and analyzes the optimal parameter settings. The results show that proper segmentation and detection methods can improve the 3D building modeling from UAV point clouds.
XXIV ISPRS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION II
(2022)
Proceedings Paper
Geography, Physical
N. Zhang, F. Nex, G. Vosselman, N. Kerle
Summary: This paper addresses the issue of deep detection networks in detecting buried victims. By generating realistic images and using an unsupervised generative adversarial network for harmonization, the accuracy of victim detection can be effectively improved.
XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III
(2022)
Article
Remote Sensing
Anne Steenbeek, Francesco Nex
Summary: This paper investigates the real-time capabilities of a commercial, inexpensive UAV for indoor mapping in emergency conditions. By integrating SLAM and CNN-based depth estimation algorithms using input images, a map of the environment suitable for real-time exploration is generated. The results demonstrate that this method meets the requirements of First Responders in exploring indoor volumes before entering the building.
Article
Environmental Sciences
Claudia Stocker, Francesco Nex, Mila Koeva, Markus Gerke