{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T11:52:18Z","timestamp":1768477938553,"version":"3.49.0"},"reference-count":33,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,1]]},"DOI":"10.1109\/imcom48794.2020.9001718","type":"proceedings-article","created":{"date-parts":[[2020,2,21]],"date-time":"2020-02-21T08:20:31Z","timestamp":1582273231000},"page":"1-8","source":"Crossref","is-referenced-by-count":10,"title":["Machine Learning in Indian Crop Classification of Temporal Multi-Spectral Satellite Image"],"prefix":"10.1109","author":[{"given":"Ravali","family":"Koppaka","sequence":"first","affiliation":[]},{"given":"Teng-Sheng","family":"Moh","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2010.11.001"},{"key":"ref32","article-title":"Accuracy, Precision, Recall or F1?","year":"2019","journal-title":"Towards Data Science"},{"key":"ref31","article-title":"Understanding Confusion Matrix","year":"2019","journal-title":"Towards Data Science"},{"key":"ref30","article-title":"Paperspace","year":"2019","journal-title":"COM papers"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2010.12.012"},{"key":"ref11","article-title":"Wheat Production Estimation Using Remote Sensing Data: An Indian Experience","author":"hooda","year":"2006","journal-title":"Compilation of ISRS WG VIII\/10 Workshop 2006 Remote Sensing Support to Crop Yield Forest and Area Estimates"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.10.434"},{"key":"ref13","article-title":"Comparison of Machine Learning Algorithms Random Forest, Artificial Neural Network and Support Vector Machine to Maximum Likelihood for Supervised Crop Type Classification","author":"nitze","year":"2012"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2016.2641240"},{"key":"ref15","article-title":"Deep learning for remote sensing image classification: A survey","author":"ying","year":"2018","journal-title":"Wires Data Mining Knowl Discov"},{"key":"ref16","article-title":"Sentinel Online","year":"0"},{"key":"ref17","article-title":"Sen2Cor","year":"0"},{"key":"ref18","first-page":"656","author":"jensen","year":"2000","journal-title":"Remote Sensing of the Environment An Earth Resource Perspective"},{"key":"ref19","year":"2019","journal-title":"What is NDVI (Normalized Difference Vegetation Index)? - GIS Geography"},{"key":"ref28","article-title":"TensorFlow","year":"2019","journal-title":"TensorFlow&#x2122;"},{"key":"ref4","first-page":"568","article-title":"Early results from crop studies using IRS 1C data","volume":"70","author":"parihar","year":"1996","journal-title":"Current Science"},{"key":"ref27","article-title":"Home - Keras Documentation","year":"2019","journal-title":"Keras io"},{"key":"ref3","author":"singh","year":"0","journal-title":"Crop Insurance in India"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1117\/12.2503653"},{"key":"ref29","author":"pumperla","year":"2016","journal-title":"Hyperas"},{"key":"ref5","first-page":"162","article-title":"Crop inventory using remotely sensed data","volume":"61","author":"navalgund","year":"1991","journal-title":"Current Science"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1126\/science.208.4445.670"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.1984.6499157"},{"key":"ref2","year":"2018"},{"key":"ref9","article-title":"Crop Area Statistics","year":"2018"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1080\/01431169208904194"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1080\/01431161.2018.1433343"},{"key":"ref22","article-title":"The Random Forest Algorithm","year":"2019","journal-title":"Towards Data Science"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2016.2641240"},{"key":"ref24","article-title":"An Introduction to Recurrent Neural Networks","year":"2019","journal-title":"Medium"},{"key":"ref23","article-title":"A Comprehensive Guide to Convolutional Neural Networks?&#x2014;?the ELI5 way","year":"2019","journal-title":"Towards Data Science"},{"key":"ref26","year":"2019"},{"key":"ref25","year":"2009","journal-title":"Open Source Geospatial Foundation"}],"event":{"name":"2020 14th International Conference on Ubiquitous Information Management and Communication (IMCOM)","location":"Taichung, Taiwan","start":{"date-parts":[[2020,1,3]]},"end":{"date-parts":[[2020,1,5]]}},"container-title":["2020 14th International Conference on Ubiquitous Information Management and Communication (IMCOM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8977604\/9001671\/09001718.pdf?arnumber=9001718","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T21:57:57Z","timestamp":1656453477000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9001718\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/imcom48794.2020.9001718","relation":{},"subject":[],"published":{"date-parts":[[2020,1]]}}}