{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:47:12Z","timestamp":1750308432683,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":10,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,10,27]],"date-time":"2018-10-27T00:00:00Z","timestamp":1540598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,10,27]]},"DOI":"10.1145\/3291801.3291839","type":"proceedings-article","created":{"date-parts":[[2019,1,14]],"date-time":"2019-01-14T13:15:25Z","timestamp":1547471725000},"page":"174-177","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Cloud Segmentation of Remote Sensing Images on Landsat-8 by Deep Learning"],"prefix":"10.1145","author":[{"given":"Xiaoshuang","family":"Zeng","sequence":"first","affiliation":[{"name":"College of Electronic Science, National University of Defense Technology, Changsha, China"}]},{"given":"Jungang","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Electronic Science, National University of Defense Technology, Changsha, China"}]},{"given":"Xinpu","family":"Deng","sequence":"additional","affiliation":[{"name":"College of Electronic Science, National University of Defense Technology, Changsha, China"}]}],"member":"320","published-online":{"date-parts":[[2018,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1175\/JTECH1875.1"},{"key":"e_1_3_2_1_2_1","first-page":"1091","article-title":"All-sky imaging: A Simple, versatile system for atmospheric research","volume":"48","author":"Kreuter A","year":"2009","unstructured":"Kreuter A , Zangerl M , Schwarzmann M , Blumthaler M. 2009 . All-sky imaging: A Simple, versatile system for atmospheric research . Change , 48 , 6(2009), 1091 -- 1097 . Kreuter A, Zangerl M, Schwarzmann M, Blumthaler M. 2009. All-sky imaging: A Simple, versatile system for atmospheric research. Change, 48, 6(2009), 1091--1097.","journal-title":"Change"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1175\/2010JTECHA1353.1"},{"key":"e_1_3_2_1_4_1","first-page":"473","article-title":"A simple method for the assessment of the cloud cover state in high-latitude regions by a ground-based digital camera","volume":"23","author":"Souzaecher MP","year":"2006","unstructured":"Souzaecher MP , Pereira EB , Bins LS , Andrade MAR . 2006 . A simple method for the assessment of the cloud cover state in high-latitude regions by a ground-based digital camera . Journal of Atmospheic & Oceanic Technology. 23 , 6(2006), 473 . Souzaecher MP, Pereira EB, Bins LS, Andrade MAR. 2006. A simple method for the assessment of the cloud cover state in high-latitude regions by a ground-based digital camera. Journal of Atmospheic & Oceanic Technology. 23, 6(2006), 473.","journal-title":"Journal of Atmospheic & Oceanic Technology."},{"key":"e_1_3_2_1_5_1","first-page":"713","article-title":"An automatic ground-based cloud detection method based on adaptive threshold","volume":"26","author":"Yang J","year":"2009","unstructured":"Yang J , Lu WT , Ma Y , Yao W. 2009 . An automatic ground-based cloud detection method based on adaptive threshold . Journal of Applied Meteorological Science. 26 , 6(2009), 713 -- 721 . Yang J, Lu WT, Ma Y, Yao W. 2009. An automatic ground-based cloud detection method based on adaptive threshold. Journal of Applied Meteorological Science. 26, 6(2009), 713--721.","journal-title":"Journal of Applied Meteorological Science."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2014.2341291"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2014.2356616"},{"key":"e_1_3_2_1_8_1","unstructured":"A. Krizhevsky I. Sutskever and G.E. Hinton. 2012. Imagenet classification with deep convolutional neural networks. Adv. neural inf. proces. Syst(2012) 1097--1105.   A. Krizhevsky I. Sutskever and G.E. Hinton. 2012. Imagenet classification with deep convolutional neural networks. Adv. neural inf. proces. Syst(2012) 1097--1105."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"}],"event":{"name":"ICBDR 2018: 2018 The 2nd International Conference on Big Data Research","sponsor":["Shandong Univ. Shandong University","University of Queensland University of Queensland","Dalian Maritime University"],"location":"Weihai China","acronym":"ICBDR 2018"},"container-title":["Proceedings of the 2nd International Conference on Big Data Research"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3291801.3291839","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3291801.3291839","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T17:49:49Z","timestamp":1750268989000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3291801.3291839"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,27]]},"references-count":10,"alternative-id":["10.1145\/3291801.3291839","10.1145\/3291801"],"URL":"https:\/\/doi.org\/10.1145\/3291801.3291839","relation":{},"subject":[],"published":{"date-parts":[[2018,10,27]]},"assertion":[{"value":"2018-10-27","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}