{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T01:18:25Z","timestamp":1775006305177,"version":"3.50.1"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031789304","type":"print"},{"value":"9783031789311","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-78931-1_13","type":"book-chapter","created":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T03:04:12Z","timestamp":1751684652000},"page":"124-132","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive DoubleU-Net for\u00a0Pothole Segmentation with\u00a0Stagnant Water Detection"],"prefix":"10.1007","author":[{"given":"Lakshmi Sai Ram","family":"Kakarla","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ayesha","family":"Shaik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A","family":"Balasundaram","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mattapally Sai","family":"Nithin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kovvuri Uday Surya Deveswar","family":"Reddy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M","family":"Nivedita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,6]]},"reference":[{"key":"13_CR1","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1007\/978-981-15-0751-9_109","volume-title":"Soft Computing: Theories and Applications","author":"S Arjapure","year":"2020","unstructured":"Arjapure, S., Kalbande, D.R.: Review on analysis techniques for road pothole detection. In: Pant, M., Sharma, T.K., Verma, O.P., Singla, R., Sikander, A. (eds.) Soft Computing: Theories and Applications, pp. 1189\u20131197. Springer Singapore, Singapore (2020)"},{"key":"13_CR2","doi-asserted-by":"publisher","first-page":"107752","DOI":"10.1016\/j.dib.2021.107752","volume":"40","author":"S Bhutad","year":"2021","unstructured":"Bhutad, S., Patil, K.: Dataset of stagnant water and wet surface label images for detection. Data Brief 40, 107752 (2021)","journal-title":"Data Brief"},{"key":"13_CR3","unstructured":"Chen, L., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Deeplab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. CoRR abs\/1606.00915 (2016). http:\/\/arxiv.org\/abs\/1606.00915"},{"key":"13_CR4","doi-asserted-by":"publisher","unstructured":"Coenen, T.B., Golroo, A.: A review on automated pavement distress detection methods. Cogent Eng. 4(1), 1374822 (2017). \n\nhttps:\/\/doi.org\/10.1080\/23311916.2017.1374822. \n\nhttps:\/\/doi.org\/10.1080\/23311916.2017.1374822","DOI":"10.1080\/23311916.2017.1374822"},{"key":"13_CR5","doi-asserted-by":"publisher","unstructured":"Fan, R., Jiao, J., Pan, J., Huang, H., Shen, S., Liu, M.: Real-time dense stereo embedded in a uav for road inspection (2019). https:\/\/doi.org\/10.48550\/ARXIV.1904.06017. https:\/\/arxiv.org\/abs\/1904.06017","DOI":"10.48550\/ARXIV.1904.06017"},{"key":"13_CR6","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition, pp. 770\u2013778 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"key":"13_CR7","doi-asserted-by":"publisher","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00745","DOI":"10.1109\/CVPR.2018.00745"},{"key":"13_CR8","doi-asserted-by":"publisher","unstructured":"Huidrom, L., Das, L.K., Sud, S.: Method for automated assessment of potholes, cracks and patches from road surface video clips. Procedia Soc. Behav. Sci. 104, 312\u2013321 (2013).https:\/\/doi.org\/10.1016\/j.sbspro.2013.11.124. https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877042813045151. 2nd Conference of Transportation Research Group of India (2nd CTRG)","DOI":"10.1016\/j.sbspro.2013.11.124"},{"key":"13_CR9","doi-asserted-by":"publisher","unstructured":"Jha, D., Riegler, M.A., Johansen, D., Halvorsen, P., Johansen, H.D.: Doubleu-net: a deep convolutional neural network for medical image segmentation (2020). https:\/\/doi.org\/10.48550\/ARXIV.2006.04868. https:\/\/arxiv.org\/abs\/2006.04868","DOI":"10.48550\/ARXIV.2006.04868"},{"key":"13_CR10","doi-asserted-by":"publisher","unstructured":"Jha, D., Smedsrud, P.H., Riegler, M.A., Johansen, D., Lange, T.D., Halvorsen, P., D.\u00a0Johansen, H.: Resunet++: an advanced architecture for medical image segmentation. In: 2019 IEEE International Symposium on Multimedia (ISM), pp. 225\u20132255 (2019). https:\/\/doi.org\/10.1109\/ISM46123.2019.00049","DOI":"10.1109\/ISM46123.2019.00049"},{"key":"13_CR11","first-page":"603","volume":"5","author":"T Kim","year":"2014","unstructured":"Kim, T., Ryu, S.: Review and analysis of pothole detection methods. J. Emerg. Trends Comput. Inf. Sci. 5, 603\u2013608 (2014)","journal-title":"J. Emerg. Trends Comput. Inf. Sci."},{"key":"13_CR12","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1061\/(ASCE)CP.1943-5487.0000232","volume":"27","author":"C Koch","year":"2013","unstructured":"Koch, C., Jog, G., Brilakis, I.: Automated pothole distress assessment using asphalt pavement video data. J. Comput. Civil Eng. 27, 370\u2013378 (2013). https:\/\/doi.org\/10.1061\/(ASCE)CP.1943-5487.0000232","journal-title":"J. Comput. Civil Eng."},{"key":"13_CR13","unstructured":"Kumar, S., Nagineni, S., Parasuraman, S.: Dirs21-dataset for indian road scenarios (2021)"},{"issue":"5","key":"13_CR14","doi-asserted-by":"publisher","first-page":"2353","DOI":"10.1109\/TITS.2015.2428655","volume":"16","author":"S Mathavan","year":"2015","unstructured":"Mathavan, S., Kamal, K., Rahman, M.: A review of three-dimensional imaging technologies for pavement distress detection and measurements. IEEE Trans. Intell. Transp. Syst. 16(5), 2353\u20132362 (2015). https:\/\/doi.org\/10.1109\/TITS.2015.2428655","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"13_CR15","doi-asserted-by":"publisher","unstructured":"Mednis, A., Strazdins, G., Zviedris, R., Kanonirs, G., Selavo, L.: Real time pothole detection using android smartphones with accelerometers. In: 2011 International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS), pp.\u00a01\u20136 (2011). https:\/\/doi.org\/10.1109\/DCOSS.2011.5982206","DOI":"10.1109\/DCOSS.2011.5982206"},{"key":"13_CR16","doi-asserted-by":"publisher","unstructured":"Moazzam, I., Kamal, K., Mathavan, S., Usman, S., Rahman, M.: Metrology and visualization of potholes using the microsoft kinect sensor. In: 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), pp. 1284\u20131291 (2013). https:\/\/doi.org\/10.1109\/ITSC.2013.6728408","DOI":"10.1109\/ITSC.2013.6728408"},{"key":"13_CR17","doi-asserted-by":"publisher","unstructured":"Prasad, M.G., Chakraborty, A., Chalasani, R., Chandran, S.: Quadcopter-based stagnant water identification. In: 2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), pp.\u00a01\u20134 (2015). https:\/\/doi.org\/10.1109\/NCVPRIPG.2015.7490049","DOI":"10.1109\/NCVPRIPG.2015.7490049"},{"key":"13_CR18","doi-asserted-by":"publisher","unstructured":"Rankin, A.L., Matthies, L.H., Bellutta, P.: Daytime water detection based on sky reflections. In: 2011 IEEE International Conference on Robotics and Automation, pp. 5329\u20135336 (2011). https:\/\/doi.org\/10.1109\/ICRA.2011.5980525","DOI":"10.1109\/ICRA.2011.5980525"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015, pp. 234\u2013241. Springer, Cham (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"13_CR20","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv 1409.1556 (2014)"},{"key":"13_CR21","doi-asserted-by":"publisher","first-page":"04017078","DOI":"10.1061\/(ASCE)CP.1943-5487.0000726","volume":"32","author":"YC Tsai","year":"2018","unstructured":"Tsai, Y.C., Chatterjee, A.: Pothole detection and classification using 3d technology and watershed method. J. Comput. Civil Eng. 32, 04017078 (2018). https:\/\/doi.org\/10.1061\/(ASCE)CP.1943-5487.0000726","journal-title":"J. Comput. Civil Eng."}],"container-title":["Lecture Notes in Networks and Systems","Hybrid Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78931-1_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:14:30Z","timestamp":1775002470000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78931-1_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031789304","9783031789311"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78931-1_13","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"6 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Hybrid Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vilnius","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lithuania","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"his2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.mirlabs.net\/his23\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}