{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T12:43:17Z","timestamp":1781354597944,"version":"3.54.1"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2023,10,31]],"date-time":"2023-10-31T00:00:00Z","timestamp":1698710400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,10,31]],"date-time":"2023-10-31T00:00:00Z","timestamp":1698710400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51875094"],"award-info":[{"award-number":["51875094"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2020GFYD023"],"award-info":[{"award-number":["2020GFYD023"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17477-1","type":"journal-article","created":{"date-parts":[[2023,10,31]],"date-time":"2023-10-31T07:02:31Z","timestamp":1698735751000},"page":"47865-47887","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Deep Learning-based drone acoustic event detection system for microphone arrays"],"prefix":"10.1007","volume":"83","author":[{"given":"Yumeng","family":"Sun","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinguang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linwei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junjie","family":"Xv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7804-4754","authenticated-orcid":false,"given":"Yu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,10,31]]},"reference":[{"key":"17477_CR1","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.patrec.2021.05.002","volume":"148","author":"H Mokayed","year":"2021","unstructured":"Mokayed H, Shivakumara P, Woon HH et al (2021) A new DCT-PCM method for license plate number detection in drone images. Pattern Recognit Lett 148:45\u201353. https:\/\/doi.org\/10.1016\/j.patrec.2021.05.002","journal-title":"Pattern Recognit Lett"},{"key":"17477_CR2","doi-asserted-by":"publisher","first-page":"106560","DOI":"10.1016\/j.compag.2021.106560","volume":"192","author":"T Jintasuttisak","year":"2022","unstructured":"Jintasuttisak T, Edirisinghe E, Elbattay A (2022) Deep neural network based date palm tree detection in drone imagery. Comput Electron Agric 192:106560. https:\/\/doi.org\/10.1016\/j.compag.2021.106560","journal-title":"Comput Electron Agric"},{"key":"17477_CR3","doi-asserted-by":"publisher","first-page":"112594","DOI":"10.1016\/j.marpolbul.2021.112594","volume":"169","author":"L Pinto","year":"2021","unstructured":"Pinto L, Andriolo U, Gon\u00e7alves G (2021) Detecting stranded macro-litter categories on drone orthophoto by a multi-class neural network. Mar Pollut Bull 169:112594. https:\/\/doi.org\/10.1016\/j.marpolbul.2021.112594","journal-title":"Mar Pollut Bull"},{"key":"17477_CR4","doi-asserted-by":"publisher","unstructured":"Ren X, Vashisht S, Aujla G S, et al (2021) Drone-edge coalesce for energy-aware and sustainable service delivery for smart city applications. Sustain Cit Soc 103505. https:\/\/doi.org\/10.1016\/j.scs.2021.103505","DOI":"10.1016\/j.scs.2021.103505"},{"key":"17477_CR5","doi-asserted-by":"publisher","DOI":"10.3390\/drones7030212","volume":"7","author":"J Zhou","year":"2023","unstructured":"Zhou J, He L, Luo H (2023) Real-time positioning method for UAVs in complex structural health monitoring scenarios. Drones 7:212. https:\/\/doi.org\/10.3390\/drones7030212","journal-title":"Drones"},{"key":"17477_CR6","doi-asserted-by":"publisher","first-page":"115563","DOI":"10.1016\/j.eswa.2021.115563","volume":"185","author":"JA Paredes","year":"2021","unstructured":"Paredes JA, \u00c1lvarez FJ, Hansard M et al (2021) A gaussian process model for UAV localization using millimetre wave radar. Expert Syst Appl 185:115563. https:\/\/doi.org\/10.1016\/j.eswa.2021.115563","journal-title":"Expert Syst Appl"},{"key":"17477_CR7","doi-asserted-by":"publisher","first-page":"107709","DOI":"10.1016\/j.patcog.2020.107709","volume":"111","author":"J Ren","year":"2021","unstructured":"Ren J, Jiang X (2021) A three-step classification framework to handle complex data distribution for radar UAV detection. Pattern Recogn 111:107709. https:\/\/doi.org\/10.1016\/j.patcog.2020.107709","journal-title":"Pattern Recogn"},{"key":"17477_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115928","volume":"187","author":"B Sazdi\u0107-Joti\u0107","year":"2022","unstructured":"Sazdi\u0107-Joti\u0107 B, Pokrajac I, Baj\u010deti\u0107 J et al (2022) Single and multiple drones detection and identification using RF based deep learning algorithm[J]. Expert Syst Appl 187:115928. https:\/\/doi.org\/10.1016\/j.eswa.2021.115928","journal-title":"Expert Syst Appl"},{"key":"17477_CR9","doi-asserted-by":"publisher","unstructured":"Khan MA, Menouar H, Khalid OM, et al (2022) Unauthorized drone detection: experiments and prototypes[C]. 2022 IEEE International Conference on Industrial Technology (ICIT). IEEE, pp 1\u20136. https:\/\/doi.org\/10.1109\/ICIT48603.2022.10002815","DOI":"10.1109\/ICIT48603.2022.10002815"},{"key":"17477_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.jestch.2021.06.008","author":"R K\u0131l\u0131\u00e7","year":"2021","unstructured":"K\u0131l\u0131\u00e7 R, Kumbasar N, Oral EA et al (2021) Drone classification using RF signal based spectral features. Eng Sci Technol Int J. https:\/\/doi.org\/10.1016\/j.jestch.2021.06.008","journal-title":"Eng Sci Technol Int J"},{"key":"17477_CR11","doi-asserted-by":"publisher","first-page":"117654","DOI":"10.1016\/j.eswa.2022.117654","volume":"206","author":"N Kumbasar","year":"2022","unstructured":"Kumbasar N, K\u0131l\u0131\u00e7 R, Oral EA et al (2022) Comparison of spectrogram, persistence spectrum and percentile spectrum based image representation performances in drone detection and classification using novel HMFFNet: hybrid model with feature Fusion Network. Expert Syst Appl 206:117654. https:\/\/doi.org\/10.1016\/j.eswa.2022.117654","journal-title":"Expert Syst Appl"},{"key":"17477_CR12","doi-asserted-by":"publisher","unstructured":"Mohammed KK, Abd El-Latif EI, El-Sayad NE, et al (2023) Radio frequency fingerprint-based drone identification and classification using Mel spectrograms and pre-trained YAMNet Neural. Internet of Things 100879.  https:\/\/doi.org\/10.48550\/arXiv.2212.01436.  Unauthorized Drone Detection: Experiments and, Prototypes","DOI":"10.48550\/arXiv.2212.01436"},{"key":"17477_CR13","doi-asserted-by":"publisher","first-page":"261","DOI":"10.3390\/drones7040261","volume":"7","author":"P Tong","year":"2023","unstructured":"Tong P, Yang X, Yang Y, Liu W, Wu P (2023) Multi-UAV collaborative absolute vision positioning and navigation: a survey and discussion. Drones 7:261. https:\/\/doi.org\/10.3390\/drones7040261","journal-title":"Drones"},{"key":"17477_CR14","doi-asserted-by":"crossref","unstructured":"Shandilya SK, Srivastav A, Yemets K et al (2023) YOLO-based segmented dataset for drone vs. bird detection for deep and machine learning algorithms. Data in Brief 50:109355","DOI":"10.1016\/j.dib.2023.109355"},{"key":"17477_CR15","doi-asserted-by":"publisher","first-page":"103226","DOI":"10.1016\/j.apacoust.2020.107205","volume":"89","author":"A Vafeiadis","year":"2020","unstructured":"Vafeiadis A et al (2020) Audio content analysis for unobtrusive event detection in smart homes. Eng Appl Artif Intell 89:103226. https:\/\/doi.org\/10.1016\/j.apacoust.2020.107205","journal-title":"Eng Appl Artif Intell"},{"key":"17477_CR16","doi-asserted-by":"publisher","unstructured":"Scholes S, Ruget A, Mora-Mart\u00edn G, Zhu F, Gyongy I, Leach J (2022) DroneSense: The identification, segmentation, and orientation detection of drones via neural networks. In IEEE Access, 10:38154\u201338164. https:\/\/doi.org\/10.1109\/ACCESS.2022.3162866","DOI":"10.1109\/ACCESS.2022.3162866"},{"key":"17477_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.apacoust.2020.107205","volume":"163","author":"A Suman","year":"2020","unstructured":"Suman A, Kumar C (2020) An approach to detect the Accident in VANETs using acoustic signal[J]. Appl Acoust 163:107205. https:\/\/doi.org\/10.1016\/j.apacoust.2020.107205","journal-title":"Appl Acoust"},{"key":"17477_CR18","doi-asserted-by":"publisher","first-page":"106559","DOI":"10.1016\/j.ecolind.2020.106559","volume":"117","author":"S Siddagangaiah","year":"2020","unstructured":"Siddagangaiah S, Chen C, Hu W et al (2020) Automatic detection of dolphin whistles and clicks based on entropy approach. Ecol Ind 117:106559. https:\/\/doi.org\/10.1016\/j.ecolind.2020.106559","journal-title":"Ecol Ind"},{"key":"17477_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.buildenv.2020.107092","volume":"181","author":"J Kim","year":"2020","unstructured":"Kim J, Min K, Jung M et al (2020) Occupant behavior monitoring and emergency event detection in single-person households using deep learning-based sound recognition[J]. Build Environ 181:107092. https:\/\/doi.org\/10.1016\/j.buildenv.2020.107092","journal-title":"Build Environ"},{"key":"17477_CR20","doi-asserted-by":"publisher","first-page":"155710","DOI":"10.1109\/ACCESS.2020.3016748","volume":"8","author":"F Meng","year":"2020","unstructured":"Meng F, Shi Y, Wang N et al (2020) Detection of respiratory sounds based on wavelet coefficients and machine learning. IEEE Access 8:155710\u2013155720. https:\/\/doi.org\/10.1109\/ACCESS.2020.3016748","journal-title":"IEEE Access"},{"key":"17477_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107465","volume":"108","author":"R Espinosa","year":"2021","unstructured":"Espinosa R, Ponce H, Guti\u00e9rrez S (2021) Click-event sound detection in automotive industry using machine\/deep learning[J]. Appl Soft Comput 108:107465. https:\/\/doi.org\/10.1016\/j.asoc.2021.107465","journal-title":"Appl Soft Comput"},{"key":"17477_CR22","doi-asserted-by":"publisher","first-page":"104012","DOI":"10.1016\/j.dsp.2023.104012","volume":"136","author":"E Akbal","year":"2023","unstructured":"Akbal E, Akbal A, Dogan S et al (2023) An automated accurate sound-based amateur drone detection method based on skinny pattern. Digit Signal Proc 136:104012. https:\/\/doi.org\/10.1016\/j.dsp.2023.104012","journal-title":"Digit Signal Proc"},{"key":"17477_CR23","doi-asserted-by":"publisher","unstructured":"Katta SS, Nandyala S, Viegas EK, AlMahmoud A (2022) Benchmarking audio-based deep learning models for detection and identification of unmanned aerial vehicles. 2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench), Milan, Italy, pp 7\u201311. https:\/\/doi.org\/10.1109\/CPS-IoTBench56135.2022.00008","DOI":"10.1109\/CPS-IoTBench56135.2022.00008"},{"key":"17477_CR24","doi-asserted-by":"publisher","unstructured":"Dong Q, Liu Y, Liu X (2022) Drone sound detection system based on feature result-level fusion using deep learning. Multimed Tools Appl 1\u201323. https:\/\/doi.org\/10.1007\/s11042-022-12964-3","DOI":"10.1007\/s11042-022-12964-3"},{"key":"17477_CR25","doi-asserted-by":"publisher","first-page":"109540","DOI":"10.1016\/j.apacoust.2023.109540","volume":"211","author":"Q Jiao","year":"2023","unstructured":"Jiao Q, Wang X, Wang L et al (2023) Audio features based ADS-CNN method for flight attitude recognition of quadrotor UAV. Appl Acoust 211:109540. https:\/\/doi.org\/10.1016\/j.apacoust.2023.109540","journal-title":"Appl Acoust"},{"key":"17477_CR26","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.sigpro.2018.07.016","volume":"153","author":"Q Huang","year":"2018","unstructured":"Huang Q, Zhang L, Fang Y (2018) Performance analysis of low-complexity MVDR beamformer in spherical harmonics domain[J]. Sig Process 153:153\u2013163. https:\/\/doi.org\/10.1016\/j.sigpro.2018.07.016","journal-title":"Sig Process"},{"key":"17477_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.apacoust.2021.107914","volume":"177","author":"T Padois","year":"2021","unstructured":"Padois T, Fischer J, Doolan C et al (2021) Acoustic imaging with conventional frequency domain beamforming and generalized cross correlation: a comparison study[J]. Appl Acoust 177:107914. https:\/\/doi.org\/10.1016\/j.apacoust.2021.107914","journal-title":"Appl Acoust"},{"issue":"4","key":"17477_CR28","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1109\/ACSSC.2008.5074426","volume":"19","author":"L Du","year":"2009","unstructured":"Du L, Yardibi T, Li J et al (2009) Review of user parameter-free robust adaptive beamforming algorithms[J]. Digit Signal Proc 19(4):567\u2013582. https:\/\/doi.org\/10.1109\/ACSSC.2008.5074426","journal-title":"Digit Signal Proc"},{"key":"17477_CR29","doi-asserted-by":"publisher","first-page":"96470F","DOI":"10.1117\/12.2194309","volume":"9647","author":"J Busset","year":"2015","unstructured":"Busset J, Perrodin F, Wellig P et al (2015) Detection and tracking of drones using advanced acoustic cameras[C]. Unmanned\/Unattended Sensors and Sensor Networks XI; and advanced free-space optical communication techniques and applications. Int Soc Opt Photon 9647:96470F. https:\/\/doi.org\/10.1117\/12.2194309","journal-title":"Int Soc Opt Photon"},{"issue":"7","key":"17477_CR30","doi-asserted-by":"publisher","first-page":"1702","DOI":"10.1109\/TSP.2003.812831","volume":"51","author":"J Li","year":"2003","unstructured":"Li J, Stoica P, Wang Z (2003) On robust Capon beamforming and diagonal loading[J]. IEEE Trans Signal Process 51(7):1702\u20131715","journal-title":"IEEE Trans Signal Process"},{"key":"17477_CR31","doi-asserted-by":"publisher","unstructured":"Meng Z (2022) Research on robust adaptive beam forming algorithm for antenna arrays. Harbin Engineering University. https:\/\/doi.org\/10.27060\/d.cnki.ghbcu.2020.001714","DOI":"10.27060\/d.cnki.ghbcu.2020.001714"},{"key":"17477_CR32","doi-asserted-by":"publisher","first-page":"125714","DOI":"10.1109\/ACCESS.2020.3007906","volume":"8","author":"X Dong","year":"2020","unstructured":"Dong X, Yin B, Cong Y et al (2020) Environment sound event classification with a two-stream convolutional neural network. IEEE Access 8:125714\u2013125721. https:\/\/doi.org\/10.1109\/ACCESS.2020.3007906","journal-title":"IEEE Access"},{"key":"17477_CR33","doi-asserted-by":"crossref","unstructured":"Milner B, Darch J, Almajai I, et al (2008) Comparing noise compensation methods for robust prediction of acoustic speech features from mfcc vectors in noise. 2008 16th European Signal Processing Conference. IEEE, pp 1\u20135","DOI":"10.1109\/ICASSP.2008.4518517"},{"issue":"7","key":"17477_CR34","doi-asserted-by":"publisher","DOI":"10.3390\/s19071733","volume":"19","author":"Y Su","year":"2019","unstructured":"Su Y, Zhang K, Wang J, Madani K (2019) Environment sound classification using a two-stream CNN based on decision-level fusion. Sensors 19(7):1733. https:\/\/doi.org\/10.3390\/s19071733","journal-title":"Sensors"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17477-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17477-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17477-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T11:24:46Z","timestamp":1715081086000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17477-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,31]]},"references-count":34,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["17477"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17477-1","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,31]]},"assertion":[{"value":"11 June 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 September 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 October 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 October 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}