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Real-Time Detection of Ground Objects Based on Unmanned Aerial Vehicle Remote Sensing with Deep Learning: Application in Excavator Detection for Pipeline Safety

Meng, Peng, Zhou, Zhang, Lu, Baumann, Du
2020 Remote Sensing  
A widely used deep-learning algorithm, namely You Only Look Once V3, is first used to train the excavator detection model on a workstation and then deployed on an embedded board that is carried by a UAV  ...  This study proposes a new approach for integrating UAV remote sensing and deep learning for the real-time detection of ground objects.  ...  Conflicts of Interest: The authors declare no conflict of interest. Remote Sens. 2020, 12, 182  ... 
doi:10.3390/rs12010182 fatcat:vh7ohdsntrbibivep3qvmgnlle

Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey, and Future Directions [article]

Reza Shakeri, Mohammed Ali Al-Garadi, Ahmed Badawy, Amr Mohamed, Tamer Khattab, Abdulla Al-Ali, Khaled A. Harras, Mohsen Guizani
2018 arXiv   pre-print
conclusions on the challenges of each application.  ...  We highlight key and versatile aspects that span the coverage and tracking of targets and infrastructure objects, energy-efficient navigation, and image analysis using machine learning for fine-grained  ...  One of the most effective learning-based paradigms is deep learning algorithms.  ... 
arXiv:1810.09729v1 fatcat:fpjvb4cezzfnhhnefcpgulnvbu

Deep Learning-Based Detection of Pipes in Industrial Environments [chapter]

Edmundo Guerra, Jordi Palacin, Zhuping Wang, Antoni Grau
2020 Industrial Robotics - New Paradigms [Working Title]  
Robust perception is generally produced through complex multimodal perception pipelines, but these kinds of methods are unsuitable for autonomous UAV deployment, given the restriction found on the platforms  ...  This chapter describes developments and experimental results produced to develop new deep learning (DL) solutions for industrial perception problems.  ...  Acknowledgements This research was funded by the Spanish Ministry of Economy, Industry and Competitiveness through Project 2016-78957-R. © 2020 The Author(s). Licensee IntechOpen.  ... 
doi:10.5772/intechopen.93164 fatcat:e6z7hhxmnzadjnuehtwg3q2of4

A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles

Dario Cazzato, Claudio Cimarelli, Jose Luis Sanchez-Lopez, Holger Voos, Marco Leo
2020 Journal of Imaging  
on RGB-based object detection.  ...  This survey presents recent advancements in 2D object detection for the case of UAVs, focusing on the differences, strategies, and trade-offs between the generic problem of object detection, and the adaptation  ...  Differently from deep learning-based control approaches that focus on reinforcement learning schemes, this family of works relies still on supervised learning, and it represents a very active research  ... 
doi:10.3390/jimaging6080078 pmid:34460693 pmcid:PMC8321148 fatcat:ds4kpheadvg6xp2fambrp6nffq

Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges

Hazim Shakhatreh, Ahmad H. Sawalmeh, Ala Al-Fuqaha, Zuochao Dou, Eyad Almaita, Issa Khalil, Noor Shamsiah Othman, Abdallah Khreishah, Mohsen Guizani
2019 IEEE Access  
Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached.  ...  We also discuss current research trends and provide future insights for potential UAV uses.  ...  One of the approaches is to employ deep learning algorithm on high definition (HD) videos to detect defects and anomalies in real time.  ... 
doi:10.1109/access.2019.2909530 fatcat:xgknpyuqazhpvferjkkdohxmtu

A survey on predicting oil spills by studying its causes using deep learning techniques

Mona Mohamed Nasr, Fahd Kamal Kamel, Yasmen Samhan Abd Elwahab
2021 Indonesian Journal of Electrical Engineering and Computer Science  
an accident but it needs a sufficient data and a powerful technique such as deep learning techniques that give very precise results and by using this tool an Intelligent Model will build to predict oil  ...  It's an important field in searching as some human lives depend on the safety of such a field, so it's so important to use a powerful technique to define these reasons as the research point in spill accidents  ...  DEEP LEARNING ALGORITHMS Deep learning is a new field of machine learning research that was introduced with the aim of moving machine learning closer to one of its original and preliminary goals, such  ... 
doi:10.11591/ijeecs.v22.i1.pp580-589 fatcat:sub5427egnfstbctdzck4w7zdi

Boost Precision Agriculture with Unmanned Aerial Vehicle Remote Sensing and Edge Intelligence: A Survey

Jia Liu, Jianjian Xiang, Yongjun Jin, Renhua Liu, Jining Yan, Lizhe Wang
2021 Remote Sensing  
Furthermore, deep learning (DL) has been successfully applied in agricultural applications such as weed detection, crop pest and disease detection, etc. as an intelligent tool.  ...  However, most DL-based methods place high computation, memory and network demands on resources.  ...  Deep Learning in Precision Agriculture with UAV Remote Sensing Deep Learning Methods in Precision Agriculture DL is a subset of artificial neural network (ANN) methods in machine learning.  ... 
doi:10.3390/rs13214387 fatcat:amrm5blon5hmhnk7arme2vsqwq

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

Maryam Pishgar, Salah Fuad Issa, Margaret Sietsema, Preethi Pratap, Houshang Darabi
2021 International Journal of Environmental Research and Public Health  
The majority of evidence of AI in OSH research within the oil/gas and transportation sectors focused on the development of sensors to detect hazardous situations.  ...  In construction the focus was on the use of sensors to detect incidents. The research in the agriculture sector focused on sensors and actuators that removed workers from hazardous conditions.  ...  Felemban et al. surveyed methods for anomalous events in the oil and gas industry, such as detection of pipeline leakage detection with emphasis on software-based methods [124] .  ... 
doi:10.3390/ijerph18136705 pmid:34206378 pmcid:PMC8296875 fatcat:rjbt6vdevre47dviox32sifkzy

Micro Air Vehicle Link (MAVLink) in a Nutshell: A Survey

Anis Koubaa, Azza Allouch, Maram Alajlan, Yasir Javed, Abdelfettah Belghith, Mohamed Khalgui
2019 IEEE Access  
To the best of our knowledge, this is the first technical survey and tutorial on the MAVLink protocol, which represents an important reference for unmanned systems users and developers.  ...  Most of the references are online tutorials and basic technical reports, and none of them presents comprehensive and systematic coverage of the protocol.  ...  In [67] , the authors developed an autonomous drone for the monitoring of oil and gas pipelines.  ... 
doi:10.1109/access.2019.2924410 fatcat:5pwbif55hbeehjveibs3lhwuwi

Final Program

2020 2020 International Conference on Unmanned Aircraft Systems (ICUAS)  
The three-day conference is preceded by a one-day Workshops/Tutorials program, which is composed of four (4) Tutorials.  ...  As in previous years, conference participants represent academia, industry, government agencies, lawyers, policy makers, manufacturers, students and end-users, all having deep interest in the state-of-the-art  ...  Simulations of UAV 3D path planning based on different target points in the point The recent advancements and accessibility of unmanned aerial vehicles (UAV), particularly hover-capable rotorcraft, have  ... 
doi:10.1109/icuas48674.2020.9214039 fatcat:7jr6chhfija47kgtwoxqmfmmoe

Deep Learning and Earth Observation to Support the Sustainable Development Goals [article]

Claudio Persello, Jan Dirk Wegner, Ronny Hänsch, Devis Tuia, Pedram Ghamisi, Mila Koeva, Gustau Camps-Valls
2021 arXiv   pre-print
This paper reviews current deep learning approaches for Earth observation data, along with their application towards monitoring and achieving the SDGs most impacted by the rapid development of deep learning  ...  The synergistic combination of deep learning models and Earth observation promises significant advances to support the sustainable development goals (SDGs).  ...  Detection and tracking of poachers is also on the rise, with approaches using thermal images at night [267] or based on deep reinforcement learning [268] .  ... 
arXiv:2112.11367v1 fatcat:7eve5dr45vcublfqyzzrccuvxa

A Comprehensive Overview of Technologies for Species and Habitat Monitoring and Conservation

José J Lahoz-Monfort, Michael J L Magrath
2021 BioScience  
We provide the first comprehensive overview of the current (2020) landscape of conservation technology, encompassing technologies for monitoring wildlife and habitats, as well as for on-the-ground conservation  ...  We describe technologies that deploy sensors that are fixed or portable, attached to vehicles (terrestrial, aquatic, or airborne) or to animals (biologging), complemented with a section on wildlife tracking  ...  traps), to novel applications of technology that are still not in widespread use (e.g., drone-based radio tracking, deep learning algorithms for automated detection of sounds or images).  ... 
doi:10.1093/biosci/biab073 pmid:34616236 pmcid:PMC8490933 fatcat:2t57ecor35aerl35wf66hx2x7e

Digitalisation of maintenance

Erkki Jantunen, Jaime Campos, Pankaj Sharma, David Baglee
2017 2017 2nd International Conference on System Reliability and Safety (ICSRS)  
. ♣ Please take care of your belongings in public area.  ...  Be aware of the strangers who offer you service, signature of charity, etc., at scenic spots. You can search more Tourist Information and Security tips online.  ...  and deep learning in hidden layer feature extraction.Our algorithm distinguishes uncertain state data with the help of Long Short-Term Memory (LSTM) networks based on pre-classification of targets using  ... 
doi:10.1109/icsrs.2017.8272846 fatcat:p2dgn3wgkzdsna4cbqrqckbxnm

A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing [article]

Ping Lang, Xiongjun Fu, Marco Martorella, Jian Dong, Rui Qin, Xianpeng Meng, Min Xie
2020 arXiv   pre-print
With the rapid development of machine learning (ML), especially deep learning, radar researchers have started integrating these new methods when solving RSP-related problems.  ...  The main applications of ML-based RSP are then analysed and structured based on the application field.  ...  Research on SAR-ATR system has increasingly absorbed attention from the researchers around the RSP community.  ... 
arXiv:2009.13702v1 fatcat:m6am73324zdwba736sn3vmph3i

A Survey on Industry 4.0 for the Oil and Gas Industry: Upstream Sector

Olakunle Elijah, Pang Ai Ling, Sharul Kamal Abdul Rahim, Tan Kim Geok, Agus Arsad, Evizal Abdul Kadir, Muslim Abdurrahman, Radzuan Junin, Augustine Agi, Mohammad Yasin Abdulfatah
2021 IEEE Access  
The market volatility in the oil and gas (O&G) sector, the dwindling demand for oil due to the impact of COVID-19, and the push for alternative greener energy are driving the need for innovation and digitization  ...  This has attracted research interest from academia and the industry in the application of industry 4.0 (I4.0) technologies in the O&G sector.  ...  [65] developed a UAV-based air monitoring system for methane (CH4) mon-itoring over the oil fields.  ... 
doi:10.1109/access.2021.3121302 fatcat:5ohmnlkrfjattcj6xdt4m2dwuq
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