{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T10:05:45Z","timestamp":1760609145858,"version":"3.37.3"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2019,7,8]],"date-time":"2019-07-08T00:00:00Z","timestamp":1562544000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,7,8]],"date-time":"2019-07-08T00:00:00Z","timestamp":1562544000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["No 731667 (MULTIDRONE)"],"award-info":[{"award-number":["No 731667 (MULTIDRONE)"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2020,5]]},"DOI":"10.1007\/s00521-019-04330-6","type":"journal-article","created":{"date-parts":[[2019,7,8]],"date-time":"2019-07-08T10:32:14Z","timestamp":1562581934000},"page":"4227-4238","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Continuous drone control using deep reinforcement learning for frontal view person shooting"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1177-9139","authenticated-orcid":false,"given":"Nikolaos","family":"Passalis","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anastasios","family":"Tefas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,7,8]]},"reference":[{"issue":"4","key":"4330_CR1","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1109\/TCST.2005.847331","volume":"13","author":"KH Ang","year":"2005","unstructured":"Ang KH, Chong G, Li Y (2005) PID control system analysis, design, and technology. IEEE Trans Control Syst Technol 13(4):559\u2013576","journal-title":"IEEE Trans Control Syst Technol"},{"issue":"6","key":"4330_CR2","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1109\/MSP.2017.2743240","volume":"34","author":"K Arulkumaran","year":"2017","unstructured":"Arulkumaran K, Deisenroth MP, Brundage M, Bharath AA (2017) Deep reinforcement learning: a brief survey. IEEE Signal Process Mag 34(6):26\u201338","journal-title":"IEEE Signal Process Mag"},{"key":"4330_CR3","unstructured":"\u00c5str\u00f6m KJ, H\u00e4gglund T, Astrom KJ (2006) Advanced PID control, vol 461. ISA-The Instrumentation, Systems, and Automation Society, Research Triangle Park, NC"},{"key":"4330_CR4","unstructured":"Brockman G, Cheung V, Pettersson L, Schneider J, Schulman J, Tang J, Zaremba W (2016) Openai gym. Technical Report. arXiv:1606.01540"},{"key":"4330_CR5","volume-title":"Applied optimal control: optimization, estimation and control","author":"AE Bryson","year":"1975","unstructured":"Bryson AE (1975) Applied optimal control: optimization, estimation and control. CRC Press, Boca Raton"},{"key":"4330_CR6","unstructured":"Chung J, Gulcehre C, Cho K, Bengio Y (2014) Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555"},{"issue":"1","key":"4330_CR7","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1186\/s13049-016-0313-5","volume":"24","author":"A Claesson","year":"2016","unstructured":"Claesson A, Fredman D, Svensson L, Ringh M, Hollenberg J, Nordberg P, Rosenqvist M, Djarv T, \u00d6sterberg S, Lennartsson J et al (2016) Unmanned aerial vehicles (drones) in out-of-hospital-cardiac-arrest. Scand J Trauma Resusc Emerg Med 24(1):124","journal-title":"Scand J Trauma Resusc Emerg Med"},{"key":"4330_CR8","unstructured":"Duan Y, Chen X, Houthooft R, Schulman J, Abbeel P (2016) Benchmarking deep reinforcement learning for continuous control. In: Proceedings of the international conference on machine learning, pp 1329\u20131338"},{"key":"4330_CR9","doi-asserted-by":"crossref","unstructured":"Finn C, Levine S (2017) Deep visual foresight for planning robot motion. In: Proceedings of the IEEE international conference on robotics and automation, pp 2786\u20132793","DOI":"10.1109\/ICRA.2017.7989324"},{"key":"4330_CR10","unstructured":"Finn C, Yu T, Fu J, Abbeel P, Levine S (2016) Generalizing skills with semi-supervised reinforcement learning. arXiv preprint arXiv:1612.00429"},{"key":"4330_CR11","unstructured":"Galvane Q, Fleureau J, Tariolle FL, Guillotel P (2017) Automated cinematography with unmanned aerial vehicles. arXiv preprint arXiv:1712.04353"},{"issue":"5","key":"4330_CR12","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1007\/s00521-016-2224-9","volume":"28","author":"A Garcia-Garcia","year":"2017","unstructured":"Garcia-Garcia A, Orts-Escolano S, Oprea S, Garcia-Rodriguez J, Azorin-Lopez J, Saval-Calvo M, Cazorla M (2017) Multi-sensor 3D object dataset for object recognition with full pose estimation. Neural Comput Appl 28(5):941\u2013952","journal-title":"Neural Comput Appl"},{"key":"4330_CR13","unstructured":"Gourier N, Hall D, Crowley JL (2004) Estimating face orientation from robust detection of salient facial features. In: ICPR international workshop on visual observation of deictic gestures. Citeseer"},{"key":"4330_CR14","doi-asserted-by":"crossref","unstructured":"Gu S, Holly E, Lillicrap T, Levine S (2017) Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates. In: Proceedings of the IEEE international conference on robotics and automation, pp 3389\u20133396","DOI":"10.1109\/ICRA.2017.7989385"},{"issue":"3","key":"4330_CR15","first-page":"334","volume":"2","author":"A Gynnild","year":"2014","unstructured":"Gynnild A (2014) The robot eye witness: extending visual journalism through drone surveillance. Digit J 2(3):334\u2013343","journal-title":"Digit J"},{"key":"4330_CR16","doi-asserted-by":"crossref","unstructured":"Hasselt HV, Guez A, Silver D (2016) Deep reinforcement learning with double q-learning. In: Proceedings of the AAAI conference on artificial intelligence, AAAI\u201916, pp 2094\u20132100. AAAI Press. http:\/\/dl.acm.org\/citation.cfm?id=3016100.3016191","DOI":"10.1609\/aaai.v30i1.10295"},{"issue":"2004","key":"4330_CR17","first-page":"41","volume":"2","author":"S Haykin","year":"2004","unstructured":"Haykin S, Network N (2004) A comprehensive foundation. Neural Netw 2(2004):41","journal-title":"Neural Netw"},{"key":"4330_CR18","unstructured":"Ioffe S, Szegedy C (2015) Batch normalization: accelerating deep network training by reducing internal covariate shift. In: Proceedings of the international conference on machine learning, pp 448\u2013456"},{"key":"4330_CR19","doi-asserted-by":"crossref","unstructured":"Kazemi V, Josephine S (2014) One millisecond face alignment with an ensemble of regression trees. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1867\u20131874","DOI":"10.1109\/CVPR.2014.241"},{"key":"4330_CR20","volume-title":"Optimal control theory: an introduction","author":"DE Kirk","year":"2012","unstructured":"Kirk DE (2012) Optimal control theory: an introduction. Courier Corporation, North Chelmsford"},{"key":"4330_CR21","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1016\/j.proeng.2012.08.208","volume":"45","author":"W Kr\u00fcll","year":"2012","unstructured":"Kr\u00fcll W, Tobera R, Willms I, Essen H, von Wahl N (2012) Early forest fire detection and verification using optical smoke, gas and microwave sensors. Procedia Eng 45:584\u2013594","journal-title":"Procedia Eng"},{"key":"4330_CR22","unstructured":"Levine S, Pastor P, Krizhevsky A, Quillen D (2016) Learning hand\u2013eye coordination for robotic grasping with large-scale data collection. In: Proceedings of the international symposium on experimental robotics, pp 173\u2013184"},{"key":"4330_CR23","unstructured":"Li Y (2017) Deep reinforcement learning: an overview. arXiv preprint arXiv:1701.07274"},{"key":"4330_CR24","unstructured":"Lillicrap TP, Hunt JJ, Pritzel A, Heess N, Erez T, Tassa Y, Silver D, Wierstra D (2015) Continuous control with deep reinforcement learning. arXiv preprint arXiv:1509.02971"},{"key":"4330_CR25","unstructured":"Mnih V, Badia AP, Mirza M, Graves A, Lillicrap T, Harley T, Silver D, Kavukcuoglu K (2016) Asynchronous methods for deep reinforcement learning. In: Proceedings of the international conference on machine learning, pp 1928\u20131937"},{"issue":"7540","key":"4330_CR26","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1038\/nature14236","volume":"518","author":"V Mnih","year":"2015","unstructured":"Mnih V, Kavukcuoglu K, Silver D, Rusu AA, Veness J, Bellemare MG, Graves A, Riedmiller M, Fidjeland AK, Ostrovski G et al (2015) Human-level control through deep reinforcement learning. Nature 518(7540):529","journal-title":"Nature"},{"issue":"4","key":"4330_CR27","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1145\/3072959.3073712","volume":"36","author":"T N\u00e4geli","year":"2017","unstructured":"N\u00e4geli T, Meier L, Domahidi A, Alonso-Mora J, Hilliges O (2017) Real-time planning for automated multi-view drone cinematography. ACM Trans Graph 36(4):132","journal-title":"ACM Trans Graph"},{"key":"4330_CR28","unstructured":"Ng AY, Harada, Russell S (1999) Policy invariance under reward transformations: theory and application to reward shaping. In: Proceedings of the international conference on machine learning"},{"key":"4330_CR29","doi-asserted-by":"crossref","unstructured":"Nousi P, Patsiouras E, Tefas A, Pitas I (2018) Convolutional neural networks for visual information analysis with limited computing resources. In: Proceedings of the IEEE international conference on image processing, pp 321\u2013325","DOI":"10.1109\/ICIP.2018.8451600"},{"key":"4330_CR30","first-page":"1063","volume":"1","author":"S Ohayon","year":"2006","unstructured":"Ohayon S, Rivlin E (2006) Robust 3D head tracking using camera pose estimation. Proc Int Confer Pattern Recognit 1:1063\u20131066","journal-title":"Proc Int Confer Pattern Recognit"},{"issue":"10","key":"4330_CR31","doi-asserted-by":"publisher","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","volume":"22","author":"SJ Pan","year":"2010","unstructured":"Pan SJ, Yang Q et al (2010) A survey on transfer learning. IEEE Trans Knowl Data Eng 22(10):1345\u20131359","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"4330_CR32","doi-asserted-by":"crossref","unstructured":"Passalis N, Tefas A (2017) Concept detection and face pose estimation using lightweight convolutional neural networks for steering drone video shooting. In: Proceedings of the European signal processing conference, pp 71\u201375","DOI":"10.23919\/EUSIPCO.2017.8081171"},{"key":"4330_CR33","doi-asserted-by":"crossref","unstructured":"Passalis N, Tefas A (2018) Deep reinforcement learning for frontal view person shooting using drones. In: Proceedings of the IEEE conference on evolving and adaptive intelligent systems, pp 1\u20138","DOI":"10.1109\/EAIS.2018.8397177"},{"key":"4330_CR34","doi-asserted-by":"crossref","unstructured":"Passalis N, Tefas A, Pitas I (2018) Efficient camera control using 2D visual information for unmanned aerial vehicle-based cinematography. In: Proceedings of the international symposium on circuits and systems (to appear)","DOI":"10.1109\/ISCAS.2018.8351050"},{"issue":"6","key":"4330_CR35","doi-asserted-by":"publisher","first-page":"1705","DOI":"10.1109\/TNNLS.2018.2872995","volume":"30","author":"N Passalis","year":"2018","unstructured":"Passalis N, Tefas A (2018) Training lightweight deep convolutional neural networks using bag-of-features pooling. IEEE Trans Neural Netw Learn Syst 30(6):1705\u20131715","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"4330_CR36","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.neucom.2019.01.046","volume":"335","author":"N Passalis","year":"2019","unstructured":"Passalis N, Tefas A (2019) Deep reinforcement learning for controlling frontal person close-up shooting. Neurocomputing 335:37\u201347","journal-title":"Neurocomputing"},{"key":"4330_CR37","unstructured":"Plappert M (2016) Keras-rl. https:\/\/github.com\/matthiasplappert\/keras-rl . Accessed 6 July 2019"},{"key":"4330_CR38","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1109\/TPAMI.2017.2781233","volume":"41","author":"R Ranjan","year":"2017","unstructured":"Ranjan R, Patel VM, Chellappa R (2017) Hyperface: a deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition. IEEE Trans Pattern Anal Mach Intell 41:121\u2013135","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"4330_CR39","volume-title":"Reinforcement learning: an introduction","author":"RS Sutton","year":"1998","unstructured":"Sutton RS, Barto AG (1998) Reinforcement learning: an introduction, vol 1. MIT Press, Cambridge"},{"issue":"1","key":"4330_CR40","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/s00521-013-1455-2","volume":"25","author":"L Tang","year":"2014","unstructured":"Tang L, Liu YJ, Tong S (2014) Adaptive neural control using reinforcement learning for a class of robot manipulator. Neural Comput Appl 25(1):135\u2013141","journal-title":"Neural Comput Appl"},{"key":"4330_CR41","first-page":"1633","volume":"10","author":"ME Taylor","year":"2009","unstructured":"Taylor ME, Stone P (2009) Transfer learning for reinforcement learning domains: a survey. J Mach Learn Res 10:1633\u20131685","journal-title":"J Mach Learn Res"},{"issue":"2","key":"4330_CR42","first-page":"26","volume":"4","author":"T Tieleman","year":"2012","unstructured":"Tieleman T, Hinton G (2012) Lecture 6.5-rmsprop: divide the gradient by a running average of its recent magnitude. COURSERA Neural Netw Mach Learn 4(2):26\u201331","journal-title":"COURSERA Neural Netw Mach Learn"},{"key":"4330_CR43","doi-asserted-by":"crossref","unstructured":"Toshev A, Szegedy C (2014) DeepPose: human pose estimation via deep neural networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1653\u20131660","DOI":"10.1109\/CVPR.2014.214"},{"key":"4330_CR44","first-page":"65","volume":"22","author":"D Triantafyllidou","year":"2017","unstructured":"Triantafyllidou D, Nousi P, Tefas A (2017) Fast deep convolutional face detection in the wild exploiting hard sample mining. Big Data Res 22:65","journal-title":"Big Data Res"},{"key":"4330_CR45","doi-asserted-by":"crossref","unstructured":"Tzelepi M, Tefas A (2017) Human crowd detection for drone flight safety using convolutional neural networks. In: Proceedings of the European signal processing conference, pp 743\u2013747","DOI":"10.23919\/EUSIPCO.2017.8081306"},{"key":"4330_CR46","first-page":"2094","volume":"16","author":"H Van Hasselt","year":"2016","unstructured":"Van Hasselt H, Guez A, Silver D (2016) Deep reinforcement learning with double Q-learning. Proc AAAI Confer Artif Intell 16:2094\u20132100","journal-title":"Proc AAAI Confer Artif Intell"},{"issue":"5","key":"4330_CR47","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1007\/s00521-014-1803-x","volume":"26","author":"CM Vong","year":"2015","unstructured":"Vong CM, Tai KI, Pun CM, Wong PK (2015) Fast and accurate face detection by sparse Bayesian extreme learning machine. Neural Comput Appl 26(5):1149\u20131156","journal-title":"Neural Comput Appl"},{"key":"4330_CR48","volume-title":"An introduction to multiagent systems","author":"M Wooldridge","year":"2009","unstructured":"Wooldridge M (2009) An introduction to multiagent systems. Wiley, New York"},{"key":"4330_CR49","doi-asserted-by":"crossref","unstructured":"Yang S, Luo P, Loy CC, Tang X (2016) Wider face: a face detection benchmark. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5525\u20135533","DOI":"10.1109\/CVPR.2016.596"},{"key":"4330_CR50","unstructured":"Zhang F, Leitner J, Milford M, Upcroft B, Corke P (2015) Towards vision-based deep reinforcement learning for robotic motion control. arXiv preprint arXiv:1511.03791"},{"issue":"6","key":"4330_CR51","first-page":"11","volume":"33","author":"JY Zhu","year":"2014","unstructured":"Zhu JY, Agarwala A, Efros AA, Shechtman E, Wang J (2014) Mirror mirror: crowdsourcing better portraits. ACM Trans Graph (SIGGRAPH Asia 2014) 33(6):11","journal-title":"ACM Trans Graph (SIGGRAPH Asia 2014)"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04330-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04330-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04330-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,23]],"date-time":"2022-09-23T04:40:36Z","timestamp":1663908036000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04330-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,8]]},"references-count":51,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2020,5]]}},"alternative-id":["4330"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04330-6","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2019,7,8]]},"assertion":[{"value":"31 October 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 June 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 July 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}