{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T05:25:07Z","timestamp":1738387507211,"version":"3.35.0"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,12,15]],"date-time":"2024-12-15T00:00:00Z","timestamp":1734220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,15]],"date-time":"2024-12-15T00:00:00Z","timestamp":1734220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s11760-024-03683-3","type":"journal-article","created":{"date-parts":[[2024,12,15]],"date-time":"2024-12-15T18:28:54Z","timestamp":1734287334000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimized deep networks for road extraction using satellite images"],"prefix":"10.1007","volume":"19","author":[{"given":"D.","family":"Subhashini","sequence":"first","affiliation":[]},{"given":"V. B. S. Srilatha Indira","family":"Dutt","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,15]]},"reference":[{"key":"3683_CR1","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1007\/s11277-018-6024-7","volume":"104","author":"S Jayanthi","year":"2019","unstructured":"Jayanthi, S., Vennila, C.: Advanced satellite image classification of various resolution image using a novel approach of deep neural network classifier. Wirel. Pers. Commun. 104, 357\u2013372 (2019). https:\/\/doi.org\/10.1007\/s11277-018-6024-7","journal-title":"Wirel. Pers. Commun."},{"key":"3683_CR2","doi-asserted-by":"publisher","first-page":"2729","DOI":"10.1007\/s11277-020-07044-4","volume":"117","author":"K Hariharan","year":"2021","unstructured":"Hariharan, K., Rajaan, N.R., Chelliah, P.P.R., Deepika, M.: The enriched feature enhancement technique for satellite image based on transforms using PCNN. Wirel. Pers. Commun. 117, 2729\u20132744 (2021). https:\/\/doi.org\/10.1007\/s11277-020-07044-4","journal-title":"Wirel. Pers. Commun."},{"key":"3683_CR3","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1007\/s11277-020-07247-9","volume":"113","author":"RC Sahoo","year":"2020","unstructured":"Sahoo, R.C., Pradhan, S.K.: An efficient approach for enhancing contrast level and segmenting satellite images: HNN and FCM approach. Wirel. Pers. Commun. 113, 651\u2013667 (2020). https:\/\/doi.org\/10.1007\/s11277-020-07247-9","journal-title":"Wirel. Pers. Commun."},{"issue":"3","key":"3683_CR4","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1007\/s12524-020-01228-y","volume":"49","author":"A Abdollahi","year":"2021","unstructured":"Abdollahi, A., Pradhan, B., Shukla, N.: Road extraction from high-resolution orthophoto images using convolutional neural network. J. Indian Soc. Remote Sens. 49(3), 569\u2013583 (2021). https:\/\/doi.org\/10.1007\/s12524-020-01228-y","journal-title":"J. Indian Soc. Remote Sens."},{"key":"3683_CR5","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1016\/j.procs.2020.03.418","volume":"167","author":"JDD Jayaseeli","year":"2020","unstructured":"Jayaseeli, J.D.D., Malathi, D.: An efficient automated road region extraction from high-resolution satellite images using improved cuckoo search with multi-level thresholding schema. Proced. Comput. Sci. 167, 1161\u20131170 (2020). https:\/\/doi.org\/10.1016\/j.procs.2020.03.418","journal-title":"Proced. Comput. Sci."},{"key":"3683_CR6","doi-asserted-by":"publisher","first-page":"581","DOI":"10.12720\/jcm.17.7.581-591","volume":"17","author":"D Subhashini","year":"2022","unstructured":"Subhashini, D., Srilatha Indira Dutt, V.B.S.: Implementation of satellite road image denoising using iterative domain guided image filtering with gray world optimization. J. Commun. 17, 581\u2013591 (2022). https:\/\/doi.org\/10.12720\/jcm.17.7.581-591","journal-title":"J. Commun."},{"key":"3683_CR7","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1007\/978-981-16-6936-1_15","volume-title":"Intelligent Infrastructure in Transportation and Management","author":"A Nohwal","year":"2022","unstructured":"Nohwal, A., Jangid, T., Panigrahi, N.: Automatic extraction of road network from satellite images of urban areas using convolution neural network. In: Intelligent Infrastructure in Transportation and Management, pp. 181\u2013192. Springer, Singapore (2022)"},{"key":"3683_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2021.3073923","volume":"60","author":"Y Xu","year":"2021","unstructured":"Xu, Y., Chen, H., Du, C., Li, J.: MSACon: mining spatial attention-based contextual information for road extraction. IEEE Trans. Geosci. Remote Sens. 60, 1\u201317 (2021). https:\/\/doi.org\/10.1109\/TGRS.2021.3073923","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"3683_CR9","doi-asserted-by":"publisher","first-page":"174317","DOI":"10.1109\/ACCESS.2020.3026084","volume":"8","author":"C Yang","year":"2020","unstructured":"Yang, C., Wang, Z.: An ensemble Wasserstein generative adversarial network method for road extraction from high-resolution remote sensing images in rural areas. IEEE Access. 8, 174317\u2013174324 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.3026084","journal-title":"IEEE Access."},{"issue":"3","key":"3683_CR10","doi-asserted-by":"publisher","first-page":"1836","DOI":"10.1109\/TGRS.2020.3003425","volume":"59","author":"J Zhang","year":"2020","unstructured":"Zhang, J., Hu, Q., Li, J., Ai, M.: Learning from GPS trajectories of floating car for CNN-based urban road extraction with high-resolution satellite imagery. IEEE Trans. Geosci. Remote Sens. 59(3), 1836\u20131847 (2020). https:\/\/doi.org\/10.1109\/TGRS.2020.3003425","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"3683_CR11","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s12145-019-00413-z","volume":"13","author":"B Yang","year":"2020","unstructured":"Yang, B., Wang, S., Zhou, Y., Wang, F., Hu, Q., Chang, Y., Zhao, Q.: Extraction of road blockage information for the Jiuzhaigou earthquake based on a convolution neural network and very-high-resolution satellite images. Earth Sci. Inf. 13(1), 115\u2013127 (2020). https:\/\/doi.org\/10.1007\/s12145-019-00413-z","journal-title":"Earth Sci. Inf."},{"key":"3683_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/LGRS.2021.3074524","volume":"19","author":"SB Chen","year":"2021","unstructured":"Chen, S.B., Ji, Y.X., Tang, J., Luo, B., Wang, W.Q., Lv, K.: DBRANet: road extraction by the dual-branch encoder and regional attention decoder. IEEE Geosci. Remote Sens. Lett. 19, 1\u20135 (2021). https:\/\/doi.org\/10.1109\/LGRS.2021.3074524","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"3683_CR13","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1007\/s12524-022-01507-w","volume":"50","author":"M Salah","year":"2022","unstructured":"Salah, M.: Extraction of road centrelines and edge lines from high-resolution satellite imagery using density-oriented Fuzzy C-means and mathematical morphology. J. Indian Soc. Remote Sens. 50, 1243\u20131255 (2022). https:\/\/doi.org\/10.1007\/s12524-022-01507-w","journal-title":"J. Indian Soc. Remote Sens."},{"issue":"06","key":"3683_CR14","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.17577\/IJERTV9IS061006","volume":"9","author":"D Subhashini","year":"2020","unstructured":"Subhashini, D.: A review on road extraction based on neural and non-neural networks. Int. J. Eng. Res. 9(06), 2278 (2020). https:\/\/doi.org\/10.17577\/IJERTV9IS061006","journal-title":"Int. J. Eng. Res."},{"key":"3683_CR15","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1016\/j.isprsjprs.2021.03.016","volume":"175","author":"Q Zhu","year":"2021","unstructured":"Zhu, Q., Zhang, Y., Wang, L., Zhong, Y., Guan, Q., Lu, X., Zhang, L., Li, D.: A global context-aware and batch-independent network for road extraction from VHR satellite imagery. ISPRS J. Photogramm. Remote Sens. 175, 353\u2013365 (2021). https:\/\/doi.org\/10.1016\/j.isprsjprs.2021.03.016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"3683_CR16","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/j.isprsjprs.2019.10.001","volume":"158","author":"C Tao","year":"2019","unstructured":"Tao, C., Qi, J., Li, Y., Wang, H., Li, H.: Spatial information inference net: road extraction using road-specific contextual information. ISPRS J. Photogramm. Remote Sens. 158, 155\u2013166 (2019). https:\/\/doi.org\/10.1016\/j.isprsjprs.2019.10.001","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"3683_CR17","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.neucom.2019.05.007","volume":"356","author":"G Cheng","year":"2019","unstructured":"Cheng, G., Wu, C., Huang, Q., Meng, Y., Shi, J., Chen, J., Yan, D.: Recognizing road from satellite images by the structured neural network. Neurocomputing 356, 131\u2013141 (2019). https:\/\/doi.org\/10.1016\/j.neucom.2019.05.007","journal-title":"Neurocomputing"},{"key":"3683_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/LGRS.2021.3050477","volume":"19","author":"Y Wang","year":"2022","unstructured":"Wang, Y., Seo, J., Jeon, T.: NL-LinkNet: toward lighter but more accurate road extraction with nonlocal operations. IEEE Geosci. Remote Sens. Lett. 19, 1\u20135 (2022). https:\/\/doi.org\/10.1109\/LGRS.2021.3050477","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"3683_CR19","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.procs.2019.01.183","volume":"147","author":"M Hong","year":"2019","unstructured":"Hong, M., Guo, J., Dai, Y., Yin, Z.: A novel FMH model for road extraction from high-resolution remote sensing images in urban areas. Proced. Comput. Sci. 147, 49\u201355 (2019). https:\/\/doi.org\/10.1016\/j.procs.2019.01.183","journal-title":"Proced. Comput. Sci."},{"issue":"5","key":"3683_CR20","doi-asserted-by":"publisher","first-page":"2689","DOI":"10.1007\/s10489-020-01900-3","volume":"51","author":"NS Punn","year":"2021","unstructured":"Punn, N.S., Agarwal, S.: Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks. Appl. Intell. 51(5), 2689\u20132702 (2021). https:\/\/doi.org\/10.1007\/s10489-020-01900-3","journal-title":"Appl. Intell."},{"key":"3683_CR21","first-page":"23","volume-title":"Nature-inspired optimizers","author":"AA Heidari","year":"2020","unstructured":"Heidari, A.A., Faris, H., Mirjalili, S., Aljarah, I., Mafarja, M.: Antlion optimizer: theory, literature review, and application in multi-layer perceptron neural networks. In: Nature-inspired optimizers, pp. 23\u201346. Springer, Cham (2020)"},{"key":"3683_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2021.3085870","volume":"60","author":"Q Shi","year":"2021","unstructured":"Shi, Q., Liu, M., Li, S., Liu, X., Wang, F., Zhang, L.: A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection. IEEE Trans. Geosci. Remote Sens. 60, 1\u201316 (2021). https:\/\/doi.org\/10.1109\/TGRS.2021.3085870","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"3683_CR23","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1016\/j.matpr.2021.08.114","volume":"60","author":"D Subhashini","year":"2022","unstructured":"Subhashini, D., Srilatha Indira Dutt, V.B.S.: An innovative hybrid technique for road extraction from noisy satellite images. Mater. Today Proceed. 60, 1229\u20131233 (2022). https:\/\/doi.org\/10.1016\/j.matpr.2021.08.114","journal-title":"Mater. Today Proceed."},{"key":"3683_CR24","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1007\/978-3-030-36808-1_31","volume-title":"International conference on neural information processing","author":"X Zhang","year":"2019","unstructured":"Zhang, X., Chen, X., Yao, L., Ge, C., Dong, M.: Deep neural network hyper parameter optimization with orthogonal array tuning. In: International conference on neural information processing, pp. 287\u2013295. Springer, Cham (2019)"},{"issue":"4","key":"3683_CR25","doi-asserted-by":"publisher","first-page":"1985","DOI":"10.1007\/s12065-020-00475-9","volume":"14","author":"TS Kavitha","year":"2021","unstructured":"Kavitha, T.S., Prasad, K.S.: Hybridizing antlion with a whale optimization algorithm for compressed sensing MR image reconstruction via l1 minimization: an ALWOA strategy. Evol. Intel. 14(4), 1985\u20131995 (2021). https:\/\/doi.org\/10.1007\/s12065-020-00475-9","journal-title":"Evol. Intel."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03683-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-024-03683-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03683-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T15:00:33Z","timestamp":1738335633000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-024-03683-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,15]]},"references-count":25,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["3683"],"URL":"https:\/\/doi.org\/10.1007\/s11760-024-03683-3","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2024,12,15]]},"assertion":[{"value":"22 May 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 August 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 September 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 December 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"135"}}