{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T06:51:00Z","timestamp":1778827860517,"version":"3.51.4"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"14","license":[{"start":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T00:00:00Z","timestamp":1626998400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T00:00:00Z","timestamp":1626998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1007\/s11042-021-11242-y","type":"journal-article","created":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T19:03:10Z","timestamp":1627066990000},"page":"19813-19834","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":61,"title":["Edge device based Military Vehicle Detection and Classification from UAV"],"prefix":"10.1007","volume":"81","author":[{"given":"Priyanka","family":"Gupta","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bhavya","family":"Pareek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7570-6292","authenticated-orcid":false,"given":"Gaurav","family":"Singal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D. Vijay","family":"Rao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,7,23]]},"reference":[{"key":"11242_CR1","unstructured":"(Accessed October 10, 2020) Camera module. https:\/\/www.raspberrypi.org\/documentation\/hardware\/camera\/"},{"key":"11242_CR2","unstructured":"(Accessed October 10, 2020) Edjeelectronics\/tensor owlite-object-detection-on-android-and-raspberrypi. https:\/\/github.com\/EdjeElectronics\/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi"},{"key":"11242_CR3","unstructured":"(Accessed October 10, 2020) Mobilenetv2: The next generation of ondevice computer vision networks. https:\/\/ai.googleblog.com\/2018\/04\/mobilenetv2-next-generation-of-on.html"},{"key":"11242_CR4","unstructured":"(Accessed October 10, 2020) Tfrecord and tf.example. https:\/\/www.tensorflow.org\/tutorials\/load_data\/tfrecord#reading_a_tfrecord_file_2"},{"key":"11242_CR5","unstructured":"(Accessed October 10, 2020) Uas photogrammetry. http:\/\/web.pdx.edu\/~jduh\/courses\/geog493f17\/Week07.pdf"},{"key":"11242_CR6","unstructured":"(Accessed October 10, 2020) Unmanned aircraft systems. https:\/\/assets.publishing.service.gov.uk\/government\/uploads\/system\/uploads\/attachment_data\/file\/673940\/doctrine_uk_uas_jdp_0_30_2.pdf"},{"key":"11242_CR7","unstructured":"Ayalew A, pooja D (2019) A review on object detection from unmanned aerial vehicle using cnn. International Journal of Advance Research, Ideas and Innovations in Technology"},{"key":"11242_CR8","doi-asserted-by":"publisher","first-page":"452","DOI":"10.3390\/electronics8040452","volume":"8","author":"V Becerra","year":"2019","unstructured":"Becerra V (2019) Autonomous control of unmanned aerial vehicles. Electronics 8:452. https:\/\/doi.org\/10.3390\/electronics8040452","journal-title":"Electronics"},{"key":"11242_CR9","unstructured":"Bochkovskiy A, Wang C-Y, Liao H-YM (2020) Yolov4: Optimal speed and accuracy of object detection"},{"key":"11242_CR10","unstructured":"Carpenter S (Accessed October 10, 2020) Fighting forest fires before they get big\u2014with drones. https:\/\/www.wired.com\/2015\/06\/fighting-forest-fores-get-big-drones\/"},{"key":"11242_CR11","doi-asserted-by":"crossref","unstructured":"Chung A, Kim S, Kwok E, Ryan M, Tan E, Gamadia R (2018) Cloud computed machine learning based real-time litter detection using micro-uav surveillance","DOI":"10.1109\/URTC45901.2018.9244800"},{"key":"11242_CR12","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","volume":"92","author":"I Colomina","year":"2014","unstructured":"Colomina I, Molina P (2014) Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS J Photogramm Remote Sens 92:79\u201397. https:\/\/doi.org\/10.1016\/j.isprsjprs.2014.02.013, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0924271614000501","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"11242_CR13","doi-asserted-by":"publisher","unstructured":"Coluccia A, Parisi G, Fascista A (2020) Detection and classification of multirotor drones in radar sensor networks: A review. Sensors 20(15). https:\/\/doi.org\/10.3390\/s20154172, https:\/\/www.mdpi.com\/1424-8220\/20\/15\/4172","DOI":"10.3390\/s20154172"},{"issue":"1","key":"11242_CR14","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1109\/TPAMI.2015.2437384","volume":"38","author":"R Girshick","year":"2016","unstructured":"Girshick R, Donahue J, Darrell T, Malik J (2016) Region-based convolutional networks for accurate object detection and segmentation. IEEE Trans Pattern Anal Mach Intell 38(1):142\u2013158","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"11242_CR15","doi-asserted-by":"publisher","unstructured":"Hadi R, Sulong G, George L (2014) Vehicle detection and tracking techniques: A concise review. Signal Image Process Int J 5. https:\/\/doi.org\/10.5121\/sipij.2013.5101","DOI":"10.5121\/sipij.2013.5101"},{"key":"11242_CR16","doi-asserted-by":"crossref","unstructured":"H\u00e4nsch R, Kaiser S, Hellwich O (2017) Near real-time object detection in rgbd data. In: VISIGRAPP","DOI":"10.5220\/0006101401790186"},{"key":"11242_CR17","doi-asserted-by":"publisher","unstructured":"Hiebert B, Nouvet E, Jeyabalan V, Donelle L (2020) The application of drones in healthcare and health-related services in north america: A scoping review. Drones 4(3). https:\/\/doi.org\/10.3390\/drones4030030, https:\/\/www.mdpi.com\/2504-446X\/4\/3\/30","DOI":"10.3390\/drones4030030"},{"key":"11242_CR18","doi-asserted-by":"crossref","unstructured":"Kamran F, Shahzad M, Shafait F (2018) Automated military vehicle detection from low-altitude aerial images. In: 2018 Digital Image Computing: Techniques and Applications (DICTA), pp 1\u20138","DOI":"10.1109\/DICTA.2018.8615865"},{"key":"11242_CR19","unstructured":"Krishnamoorthi R (2018) Quantizing deep convolutional networks for efficient inference: A whitepaper. CoRR arXiv:1806.08342"},{"key":"11242_CR20","unstructured":"Kwon Y (Accessed October 10, 2020). https:\/\/github.com\/developer0hye\/Yolo_Label"},{"key":"11242_CR21","doi-asserted-by":"crossref","unstructured":"Kyrkou C, Plastiras G, Theocharides T, Venieris S I, Bouganis C (2018) Dronet: Efficient convolutional neural network detector for real-time uav applications. In: 2018 Design, Automation Test in Europe Conference Exhibition (DATE), pp 967\u2013972","DOI":"10.23919\/DATE.2018.8342149"},{"key":"11242_CR22","doi-asserted-by":"crossref","unstructured":"Lee J, Wang J, Crandall D, \u0160abanovi\u0107 S, Fox G (2017) Real-time, cloud-based object detection for unmanned aerial vehicles. In: 2017 First IEEE International Conference on Robotic Computing (IRC), pp 36\u201343","DOI":"10.1109\/IRC.2017.77"},{"key":"11242_CR23","doi-asserted-by":"crossref","unstructured":"Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu C-Y, Berg A (2016) Ssd: Single shot multibox detector, vol 9905, pp 21\u201337","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"11242_CR24","unstructured":"MobileFirstLLC (Accessed October 10, 2020) Download all images - chrome extension. https:\/\/chrome.google.com\/webstore\/detail\/download-all-images\/ifipmflagepipjokmbdecpmjbibjnakm"},{"key":"11242_CR25","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1016\/j.procs.2018.07.063","volume":"133","author":"U Mogili","year":"2018","unstructured":"Mogili U, Deepak B (2018) Review on application of drone systems in precision agriculture. Procedia Comput Sci 133:502\u2013509. https:\/\/doi.org\/10.1016\/j.procs.2018.07.063","journal-title":"Procedia Comput Sci"},{"key":"11242_CR26","unstructured":"Ramprasath M, Hariharan S, Anand MV (2018) Image classification using convolutional neural networks"},{"issue":"2","key":"11242_CR27","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1299\/jsdd.1.120","volume":"1","author":"K NONAMI","year":"2007","unstructured":"NONAMI K (2007) Prospect and recent research &; development for civil use autonomous unmanned aircraft as uav and mav. J Syst Des Dyn 1 (2):120\u2013128. https:\/\/doi.org\/10.1299\/jsdd.1.120","journal-title":"J Syst Des Dyn"},{"key":"11242_CR28","doi-asserted-by":"crossref","unstructured":"Pareek B, Gupta P, Singal G, Kushwaha R (2019) Person identification using autonomous drone through resource constraint devices. In: 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS), pp 124\u2013129","DOI":"10.1109\/IOTSMS48152.2019.8939254"},{"key":"11242_CR29","doi-asserted-by":"crossref","unstructured":"Piras M, Grasso N, Jabbar AA (2017) Uav photogrammetric solution using a raspberry pi camera module and smart devices: Test and results","DOI":"10.5194\/isprs-archives-XLII-2-W6-289-2017"},{"issue":"1","key":"11242_CR30","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1007322005825","volume":"28","author":"L Pratt","year":"1997","unstructured":"Pratt L, Thrun S (1997) Guest editors\u2019 introduction. Mach Learn 28(1):5\u20135. https:\/\/doi.org\/10.1023\/A:1007322005825","journal-title":"Mach Learn"},{"key":"11242_CR31","doi-asserted-by":"crossref","unstructured":"Redmon J, Divvala S, Girshick R, Farhadi A (2016) You only look once: Unified, real-time object detection, pp 779\u2013788","DOI":"10.1109\/CVPR.2016.91"},{"key":"11242_CR32","unstructured":"Redmon J, Farhadi A (2018) Yolov3: An incremental improvement. arXiv:1804.02767"},{"key":"11242_CR33","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2015","unstructured":"Ren S, He K, Girshick RB, Sun J (2015) Faster r-cnn: Towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39:1137\u20131149","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"11242_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2018\/3598316","volume":"2018","author":"Y Ren","year":"2018","unstructured":"Ren Y, Zhu C, Xiao S (2018) Object detection based on fast\/faster rcnn employing fully convolutional architectures. Math Probl Eng 2018:1\u20137. https:\/\/doi.org\/10.1155\/2018\/3598316","journal-title":"Math Probl Eng"},{"key":"11242_CR35","doi-asserted-by":"crossref","unstructured":"Sandler M, Howard AG, Zhu M, Zhmoginov A, Chen L-C (2018) Inverted residuals and linear bottlenecks: Mobile networks for classification, detection and segmentation. CoRR arXiv:1801.04381","DOI":"10.1109\/CVPR.2018.00474"},{"key":"11242_CR36","unstructured":"Scheck LCW (Accessed October 10, 2020) Lawrence sperry: Genius on autopilot. https:\/\/www.historynet.com\/lawrence-sperry-autopilot-inventor-and-aviation-innovator.htm"},{"key":"11242_CR37","doi-asserted-by":"crossref","unstructured":"Singh A, Patil D, Omkar SN (2018) Eye in the sky: Real-time drone surveillance system (DSS) for violent individuals identification using scatternet hybrid deep learning network. CoRR arXiv:1806.00746","DOI":"10.1109\/CVPRW.2018.00214"},{"key":"11242_CR38","doi-asserted-by":"publisher","unstructured":"Thiels C, Aho J, Zietlow S, Jenkins D (2015) Use of unmanned aerial vehicles for medical product transport. Air Med J 34. https:\/\/doi.org\/10.1016\/j.amj.2014.10.011","DOI":"10.1016\/j.amj.2014.10.011"},{"key":"11242_CR39","unstructured":"Torrey L, Shavlik J (Accessed October 10, 2020) Transfer learning. https:\/\/www.igi-global.com\/chapter\/transfer-learning\/36988"},{"key":"11242_CR40","doi-asserted-by":"crossref","unstructured":"Verdhan V, Verdhan V (2021) Object detection using deep learning. Computer Vision Using Deep Learning: Neural Network Architectures with Python and Keras, pp 141\u2013185","DOI":"10.1007\/978-1-4842-6616-8_5"},{"issue":"1","key":"11242_CR41","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/s40537-016-0043-6","volume":"3","author":"K Weiss","year":"2016","unstructured":"Weiss K, Khoshgoftaar D (2016) A survey of transfer learning. J Big Data 3(1):9. https:\/\/doi.org\/10.1186\/s40537-016-0043-6","journal-title":"J Big Data"},{"key":"11242_CR42","doi-asserted-by":"publisher","first-page":"123757","DOI":"10.1109\/ACCESS.2019.2928603","volume":"7","author":"D Xiao","year":"2019","unstructured":"Xiao D, Shan F, Li Z, Le B T, Liu X, Li X (2019) A target detection model based on improved tiny-yolov3 under the environment of mining truck. IEEE Access 7:123757\u2013123764","journal-title":"IEEE Access"},{"key":"11242_CR43","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/j.imavis.2017.09.008","volume":"69","author":"Z Yang","year":"2018","unstructured":"Yang Z, Pun-Cheng LSC (2018) Vehicle detection in intelligent transportation systems and its applications under varying environments: A review. Image Vis Comput 69:143\u2013154. https:\/\/doi.org\/10.1016\/j.imavis.2017.09.008, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0262885617301592","journal-title":"Image Vis Comput"},{"key":"11242_CR44","doi-asserted-by":"crossref","unstructured":"Yujun Yang, Jianping Li, Yimei Yang (2015) The research of the fast svm classifier method. In: 2015 12th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), pp 121\u2013124","DOI":"10.1109\/ICCWAMTIP.2015.7493959"},{"key":"11242_CR45","doi-asserted-by":"crossref","unstructured":"Zaheer Z, Usmani A, Khan E, Qadeer MA (2016) Aerial surveillance system using uav. 2016 Thirteenth International Conference on Wireless and Optical Communications Networks (WOCN), pp 1\u20137","DOI":"10.1109\/WOCN.2016.7759885"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-11242-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-021-11242-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-11242-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T08:18:34Z","timestamp":1653034714000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-021-11242-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,23]]},"references-count":45,"journal-issue":{"issue":"14","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["11242"],"URL":"https:\/\/doi.org\/10.1007\/s11042-021-11242-y","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,23]]},"assertion":[{"value":"15 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 May 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 July 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 July 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}