{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T03:54:18Z","timestamp":1774410858984,"version":"3.50.1"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,1,30]],"date-time":"2022-01-30T00:00:00Z","timestamp":1643500800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,30]],"date-time":"2022-01-30T00:00:00Z","timestamp":1643500800000},"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":["Earth Sci Inform"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s12145-021-00746-8","type":"journal-article","created":{"date-parts":[[2022,1,30]],"date-time":"2022-01-30T00:03:36Z","timestamp":1643501016000},"page":"553-561","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Object detection in satellite images by faster R-CNN incorporated with enhanced ROI pooling (FrRNet-ERoI) framework"],"prefix":"10.1007","volume":"15","author":[{"given":"A. Azhagu Jaisudhan","family":"Pazhani","sequence":"first","affiliation":[]},{"given":"C.","family":"Vasanthanayaki","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,30]]},"reference":[{"key":"746_CR1","first-page":"150","volume-title":"Asian conference on computer vision","author":"SM Azimi","year":"2018","unstructured":"Azimi SM, Vig E, Bahmanyar R, K\u00f6rner M, Reinartz P (2018) Towards multi-class object detection in unconstrained remote sensing imagery. In: Asian conference on computer vision. Springer, Cham, pp 150\u2013165"},{"issue":"10","key":"746_CR2","doi-asserted-by":"publisher","first-page":"6508","DOI":"10.1109\/TGRS.2013.2296782","volume":"52","author":"X Bai","year":"2014","unstructured":"Bai X, Zhang H, Zhou J (2014) VHR object detection based on structural feature extraction and query expansion. IEEE Trans Geosci Remote Sens 52(10):6508\u20136520","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"10","key":"746_CR3","doi-asserted-by":"publisher","first-page":"6627","DOI":"10.1109\/TGRS.2014.2299540","volume":"52","author":"A \u00c7a\u011flar","year":"2014","unstructured":"\u00c7a\u011flar A, Aksoy S (2014) Detection of compound structures using a Gaussian mixture model with spectral and spatial constraints. IEEE Trans Geosci Remote Sens 52(10):6627\u20136638","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"10","key":"746_CR4","doi-asserted-by":"publisher","first-page":"1797","DOI":"10.1109\/LGRS.2014.2309695","volume":"11","author":"X Chen","year":"2014","unstructured":"Chen X, Xiang S, Liu C-L, Pan C-H (2014) Vehicle detection in satellite images by hybrid deep convolutional neural networks. IEEE Geosci Remote Sens Lett 11(10):1797\u20131801","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"746_CR5","doi-asserted-by":"crossref","unstructured":"Chen Y, Gao J, Zhang K (2020) R-CNN-based satellite components detection in optical images. Int J Aerospace Eng","DOI":"10.1155\/2020\/8816187"},{"key":"746_CR6","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.isprsjprs.2016.03.014","volume":"117","author":"G Cheng","year":"2016","unstructured":"Cheng G, Han J (2016) A survey on object detection in optical remote sensing images. ISPRS J Photogramm Remote Sens 117:11\u201328","journal-title":"ISPRS J Photogramm Remote Sens"},{"issue":"1","key":"746_CR7","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1080\/01431161.2012.705443","volume":"34","author":"G Cheng","year":"2013","unstructured":"Cheng G, Guo L, Zhao T, Han J, Li H, Fang J (2013) Automatic landslide detection from remote-sensing imagery using a scene classification method based on BoVW and pLSA. Int J Remote Sens 34(1):45\u201359","journal-title":"Int J Remote Sens"},{"issue":"12","key":"746_CR8","doi-asserted-by":"publisher","first-page":"7405","DOI":"10.1109\/TGRS.2016.2601622","volume":"54","author":"G Cheng","year":"2016","unstructured":"Cheng G, Zhou P, Han J (2016) Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images. IEEE Trans Geosci Remote Sens 54(12):7405\u20137415","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"746_CR9","first-page":"1440","volume-title":"Proceedings of the IEEE international conference on computer vision","author":"R Girshick","year":"2015","unstructured":"Girshick R (2015) Fast r-cnn. In: Proceedings of the IEEE international conference on computer vision, pp 1440\u20131448"},{"key":"746_CR10","first-page":"580","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"R Girshick","year":"2014","unstructured":"Girshick R, Donahue J, Darrell T, Malik J (2014) Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 580\u2013587"},{"key":"746_CR11","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.neucom.2015.09.116","volume":"187","author":"Y Guo","year":"2016","unstructured":"Guo Y, Liu Y, Oerlemans A, Lao S, Song W, Lew MS (2016) Deep learning for visual understanding: a review. Neurocomputing 187:27\u201348","journal-title":"Neurocomputing"},{"issue":"9","key":"746_CR12","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","volume":"37","author":"K He","year":"2015","unstructured":"He K, Zhang X, Ren S, Sun J (2015) Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans Pattern Anal Mach Intell 37(9):1904\u20131916","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"746_CR13","first-page":"44","volume":"7","author":"MJ Khan","year":"2017","unstructured":"Khan MJ, Yousaf A, Javed N, Nadeem S, Khurshid K (2017) Automatic target detection in satellite images using deep learning. J Space Technol 7(1):44\u201349","journal-title":"J Space Technol"},{"key":"746_CR14","first-page":"1097","volume":"25","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. Adv Neural Inf Proces Syst 25:1097\u20131105","journal-title":"Adv Neural Inf Proces Syst"},{"key":"746_CR15","first-page":"2117","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"T-Y Lin","year":"2017","unstructured":"Lin T-Y, Doll\u00e1r P, Girshick R, He K, Hariharan B, Belongie S (2017) Feature pyramid networks for object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition. IEEE Service Center, Piscataway, pp 2117\u20132125"},{"key":"746_CR16","first-page":"65","volume":"13","author":"AS Mahmoud","year":"2020","unstructured":"Mahmoud AS, Mohamed S, El-Khoribi R, Abdelsalam H (2020) Object detection using adaptive mask RCNN in optical remote sensing images. Int J Intell Eng Syst 13:65\u201376","journal-title":"Int J Intell Eng Syst"},{"issue":"6","key":"746_CR17","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2016","unstructured":"Ren S, He K, Girshick R, Sun J (2016) Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137\u20131149","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"746_CR18","doi-asserted-by":"crossref","unstructured":"Ren Y, Zhu C, Xiao S (2018) Object detection based on fast\/faster RCNN employing fully convolutional architectures. Math Probl Eng","DOI":"10.1155\/2018\/3598316"},{"key":"746_CR19","unstructured":"Simonyan K, Zisserman A, (2014) Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556."},{"issue":"8","key":"746_CR20","doi-asserted-by":"publisher","first-page":"2827","DOI":"10.1080\/01431161.2020.1826059","volume":"42","author":"Z Song","year":"2021","unstructured":"Song Z, Sui H, Hua L (2021) A hierarchical object detection method in large-scale optical remote sensing satellite imagery using saliency detection and CNN. Int J Remote Sens 42(8):2827\u20132847","journal-title":"Int J Remote Sens"},{"issue":"2","key":"746_CR21","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/s11263-013-0620-5","volume":"104","author":"JRR Uijlings","year":"2013","unstructured":"Uijlings JRR, Van De Sande KEA, Gevers T, Smeulders AWM (2013) Selective search for object recognition. Int J Comput Vis 104(2):154\u2013171","journal-title":"Int J Comput Vis"},{"key":"746_CR22","first-page":"3974","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"G-S Xia","year":"2018","unstructured":"Xia G-S, Bai X, Ding J, Zhu Z, Belongie S, Luo J, Datcu M, Pelillo M, Zhang L (2018) DOTA: A large-scale dataset for object detection in aerial images. In: Proceedings of the IEEE conference on computer vision and pattern recognition. IEEE Service Center, Piscataway, pp 3974\u20133983"},{"key":"746_CR23","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/978-3-642-12538-6_6","volume-title":"Nature inspired cooperative strategies for optimization (NICSO 2010)","author":"X-S Yang","year":"2010","unstructured":"Yang X-S (2010) A new metaheuristic bat-inspired algorithm. In: Nature inspired cooperative strategies for optimization (NICSO 2010). Springer, Berlin, Heidelberg, pp 65\u201374"},{"issue":"3","key":"746_CR24","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1504\/IJBIC.2013.055093","volume":"5","author":"X-S Yang","year":"2013","unstructured":"Yang X-S, He X (2013) Bat algorithm: literature review and applications. Int J Bio-Inspired Comput 5(3):141\u2013149","journal-title":"Int J Bio-Inspired Comput"},{"issue":"1","key":"746_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11220-020-00314-2","volume":"21","author":"S Yin","year":"2020","unstructured":"Yin S, Li H, Teng L (2020) Airport detection based on improved faster RCNN in large scale remote sensing images. Sensing Imaging 21(1):1\u201313","journal-title":"Sensing Imaging"},{"issue":"10","key":"746_CR26","doi-asserted-by":"publisher","first-page":"4895","DOI":"10.1109\/JSTARS.2015.2467377","volume":"8","author":"L Zhang","year":"2015","unstructured":"Zhang L, Shi Z, Jun W (2015) A hierarchical oil tank detector with deep surrounding features for high-resolution optical satellite imagery. IEEE J Select Topics Appl Earth Observat Remote Sensing 8(10):4895\u20134909","journal-title":"IEEE J Select Topics Appl Earth Observat Remote Sensing"},{"issue":"9","key":"746_CR27","doi-asserted-by":"publisher","first-page":"5553","DOI":"10.1109\/TGRS.2016.2569141","volume":"54","author":"F Zhang","year":"2016","unstructured":"Zhang F, Bo D, Zhang L, Miaozhong X (2016) Weakly supervised learning based on coupled convolutional neural networks for aircraft detection. IEEE Trans Geosci Remote Sens 54(9):5553\u20135563","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"4","key":"746_CR28","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1007\/s11045-015-0370-3","volume":"27","author":"P Zhou","year":"2016","unstructured":"Zhou P, Cheng G, Liu Z, Shuhui B, Xintao H (2016) Weakly supervised target detection in remote sensing images based on transferred deep features and negative bootstrapping. Multidim Syst Sign Process 27(4):925\u2013944","journal-title":"Multidim Syst Sign Process"}],"container-title":["Earth Science Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-021-00746-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12145-021-00746-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-021-00746-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,10]],"date-time":"2022-02-10T02:17:55Z","timestamp":1644459475000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12145-021-00746-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,30]]},"references-count":28,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["746"],"URL":"https:\/\/doi.org\/10.1007\/s12145-021-00746-8","relation":{},"ISSN":["1865-0473","1865-0481"],"issn-type":[{"value":"1865-0473","type":"print"},{"value":"1865-0481","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,30]]},"assertion":[{"value":"27 April 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 December 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}