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JCR Impact Factor: 0.699
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  3/2016 - 14

Control and Optimization of UAV Trajectory for Aerial Coverage in Photogrammetry Applications

POPESCU, D. See more information about POPESCU, D. on SCOPUS See more information about POPESCU, D. on IEEExplore See more information about POPESCU, D. on Web of Science, STOICAN, F. See more information about  STOICAN, F. on SCOPUS See more information about  STOICAN, F. on SCOPUS See more information about STOICAN, F. on Web of Science, ICHIM, L. See more information about ICHIM, L. on SCOPUS See more information about ICHIM, L. on SCOPUS See more information about ICHIM, L. on Web of Science
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Download PDF pdficon (1,184 KB) | Citation | Downloads: 285 | Views: 988

Author keywords
digital photography, optimization, path planning, position control, unmanned aerial vehicles

References keywords
control(10), remote(7), systems(6), unmanned(5), aerial(5), vehicle(4), trajectory(4), system(4), sensing(4), flood(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-08-31
Volume 16, Issue 3, Year 2016, On page(s): 99 - 106
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.03014
Web of Science Accession Number: 000384750000014
SCOPUS ID: 84991093546

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Photogrammetry is a well-studied and much-used analysis tool. Typical use cases include area surveillance, flood monitoring and related tasks. Usually, an Unmanned Aerial System (UAS) is used as support for image acquisition from an a priori delimited region in a semi-automated manner (via a mix of ground control and autonomous trajectory tracking). This in turn has led to various algorithms which handle path trajectory generation under realistic constraints but still many avenues remain open. In this paper, we consider typical costs and constraints (UAS dynamics, total-path length, line inter-distance, turn points, etc.) in order to obtain, via optimization procedures, an optimal trajectory. To this end we make use of polyhedral set operations, flat trajectory generation and other similar tools. Additional work includes the study of non-convex regions and estimation of the number of photographs taken via Ehrhart polynomial computations.

References | Cited By  «-- Click to see who has cited this paper

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[2] H. Khurshid, M. F. Khan, "Segmentation and Classification Using Logistic Regression in Remote Sensing Imagery," IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., vol. 8, no. 1, pp. 224-232, 2015.
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[3] R. Koschitzki, E. Schwalbe, H. Maas, "An autonomous image based approach for detecting glacial lake outburst floods," ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., vol. 1, pp. 337-342, 2014.
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[6] M. Abdelkader, M. Shaqura, C. G. Claudel, W. Gueaieb, "A UAV based system for real time flash flood monitoring in desert environments using Lagrangian microsensors," in International Conference on Unmanned Aircraft Systems (ICUAS), 2013, pp. 25-34.
[CrossRef] [SCOPUS Times Cited 27]

[7] C. Achille, A. Adami, S. Chiarini, S. Cremonesi, F. Fassi, L. Fregonese, L. Taffurelli, "UAV-based photogrammetry and integrated technologies for architectural applications-methodological strategies for the after-quake survey of vertical structures in Mantua (Italy)," Sensors, vol. 15, no. 7, pp. 15520-15539, 2015.
[CrossRef] [Web of Science Times Cited 26] [SCOPUS Times Cited 39]

[8] Q. Feng, J. Liu, J. Gong, "Urban flood mapping based on Unmanned Aerial Vehicle remote sensing and random forest classifier-A case of Yuyao, China," Water, vol. 7, no. 4, pp. 1437-1455, 2015.
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[9] S. Siebert, J. Teizer, "Mobile 3D mapping for surveying earthwork projects using an Unmanned Aerial Vehicle (UAV) system," Autom. Constr., vol. 41, pp. 1-14, 2014.
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[CrossRef] [Web of Science Times Cited 71] [SCOPUS Times Cited 76]

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[CrossRef] [SCOPUS Times Cited 45]

[13] B. Ruzgiene, T. Berteska, S. Gecyte, E. Jakubauskiene, V. C. Aksamitauskas, "The surface modelling based on UAV Photogrammetry and qualitative estimation," Measurement, 2015.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 28]

[14] D. Popescu, L. Ichim, T. Caramihale, "Flood areas detection based on UAV surveillance system, 19th International Conference on System Theory, Control and Computing (ICSTCC), pp. 753-758, 2015.
[CrossRef] [SCOPUS Times Cited 6]

[15] S. M. Adams, C. J. Friedland, "A survey of unmanned aerial vehicle (UAV) usage for imagery collection in disaster research and management," in 9th International Workshop on Remote Sensing for Disaster Response, 2011.

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[19] I. Prodan, S. Olaru, R. Bencatel, J. B. De Sousa, C. Stoica, S.-I. Niculescu, "Receding horizon flight control for trajectory tracking of autonomous aerial vehicles," Control Eng. Pract., vol. 21, no. 10, pp. 1334-1349, 2013.
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[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 3]

References Weight

Web of Science® Citations for all references: 339 TCR
SCOPUS® Citations for all references: 567 TCR

Web of Science® Average Citations per reference: 12 ACR
SCOPUS® Average Citations per reference: 20 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-10-20 22:16 in 121 seconds.

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

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