{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T06:12:34Z","timestamp":1742969554279,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031104633"},{"type":"electronic","value":"9783031104640"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-10464-0_9","type":"book-chapter","created":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T13:04:06Z","timestamp":1657112646000},"page":"117-128","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Neural Networks for\u00a0Remote Sensing Image Classification"],"prefix":"10.1007","author":[{"given":"Giorgia","family":"Miniello","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"La Salandra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gioacchino","family":"Vino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,7]]},"reference":[{"key":"9_CR1","doi-asserted-by":"publisher","first-page":"073001","DOI":"10.1088\/1748-9326\/ab1b7d","volume":"14","author":"AY Sun","year":"2019","unstructured":"Sun, A.Y., Scanlon, B.R.: How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions. Environ. Res. Lett. 14, 073001 (2019)","journal-title":"Environ. Res. Lett."},{"issue":"1","key":"9_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5721\/EuJRS20124501","volume":"45","author":"CR Fichera","year":"2012","unstructured":"Fichera, C.R., Modica, G., Pollino, M.: Land Cover classification and change-detection analysis using multi-temporal remote sensed imagery and landscape metrics. Eur. J. Remote Sens. 45(1), 1\u20138 (2012). https:\/\/doi.org\/10.5721\/EuJRS20124501","journal-title":"Eur. J. Remote Sens."},{"key":"9_CR3","unstructured":"https:\/\/www.dtascarl.org\/progettidta\/close-to-the-earth\/"},{"key":"9_CR4","unstructured":"https:\/\/www.dtascarl.org\/progettidta\/rpasinair\/"},{"key":"9_CR5","doi-asserted-by":"publisher","first-page":"102600","DOI":"10.1016\/j.jag.2021.102600","volume":"105","author":"M La Salandra","year":"2021","unstructured":"La Salandra, M., et al.: Generating UAV high-resolution topographic data within a FOSS photogrammetric workflow using high-performance computing clusters. Int. J. Appl. Earth Observ. Geoinf. 105, 102600 (2021). https:\/\/doi.org\/10.1016\/j.jag.2021.102600","journal-title":"Int. J. Appl. Earth Observ. Geoinf."},{"key":"9_CR6","unstructured":"https:\/\/www.recas-bari.it"},{"key":"9_CR7","doi-asserted-by":"publisher","first-page":"2217","DOI":"10.1109\/JSTARS.2019.2918242","volume":"12","author":"P Helber","year":"2019","unstructured":"Helber, P., Bischke, B., Dengel, A., Borth, D.: Eurosat: a novel dataset and deep learning benchmark for land use and land cover classification. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 12, 2217\u20132226 (2019)","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Miniello, G., La Salandra, M.: A new method for geomorphological studies and land cover classification using Machine Learning techniques. PoS(ISGC2021)031 (2021)","DOI":"10.22323\/1.378.0031"},{"key":"9_CR9","unstructured":"https:\/\/keras.io\/api\/layers\/pooling_layers\/max_pooling2d\/"},{"key":"9_CR10","unstructured":"https:\/\/keras.eio\/api\/applications\/vgg\/"},{"key":"9_CR11","doi-asserted-by":"publisher","unstructured":"Vandana, S.: Land Cover classification using machine learning techniques - a survey. Int. J. Eng. Tech. Res. 9(06) (2020). https:\/\/doi.org\/10.17577\/IJERTV9IS060881","DOI":"10.17577\/IJERTV9IS060881"},{"key":"9_CR12","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: International Conference on Learning Representations. arXiv:1409.1556 (2015)"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-10464-0_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,14]],"date-time":"2022-09-14T14:04:03Z","timestamp":1663164243000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-10464-0_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031104633","9783031104640"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-10464-0_9","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"7 July 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Science and Information Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 July 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 July 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sai2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/saiconference.com\/Computing","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}