{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:15:02Z","timestamp":1750220102862,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":25,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,6,24]],"date-time":"2022-06-24T00:00:00Z","timestamp":1656028800000},"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":[[2022,6,24]]},"DOI":"10.1145\/3548608.3559275","type":"proceedings-article","created":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T17:47:01Z","timestamp":1665769621000},"page":"625-630","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Crop Recognition Method Based on Gradient Features and Multilayer Perceptron with Application to Maize Recognition"],"prefix":"10.1145","author":[{"given":"Lixing","family":"Xu","sequence":"first","affiliation":[{"name":"College of Computer and Information Engineering, Inner Mongolia Agricultural University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Gao","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Inner Mongolia Agricultural University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junjie","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Inner Mongolia Agricultural University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanying","family":"Bai","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingzheng","family":"Shen","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Inner Mongolia Agricultural University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,10,14]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Pan Z.Q. Liu G.H. Zhou C.H.(2003) The crop distribution of Yellow River Delta using remote sensing method. J. Geographical Research (06): 799-806+814.  Pan Z.Q. Liu G.H. Zhou C.H.(2003) The crop distribution of Yellow River Delta using remote sensing method. J. Geographical Research (06): 799-806+814."},{"issue":"10","key":"e_1_3_2_1_2_1","first-page":"1808","article-title":"Extraction of main crops in Yellow River Delta based on MODIS NDVI Time Series","volume":"32","author":"Guo Y.S.","year":"2017","unstructured":"Guo , Y.S. , Liu , Q.S. , Liu , G.H. , ( 2017 ) Extraction of main crops in Yellow River Delta based on MODIS NDVI Time Series . J. Journal of Natural Resources , 32 ( 10 ): 1808 - 1818 . Guo,Y.S., Liu,Q.S., Liu,G.H., (2017) Extraction of main crops in Yellow River Delta based on MODIS NDVI Time Series. J. Journal of Natural Resources, 32(10): 1808-1818.","journal-title":"J. Journal of Natural Resources"},{"issue":"04","key":"e_1_3_2_1_3_1","first-page":"158","article-title":"Research on crop classification based on GF-2 Satellite","volume":"44","author":"Cao W.N.","year":"2021","unstructured":"Cao , W.N. , Wang , W.G. , Wang , X. , ( 2021 ) Research on crop classification based on GF-2 Satellite . J. Geomatics and Spatial Information Technology , 44 ( 04 ): 158 - 161 . Cao,W.N.,Wang,W.G.,Wang,X.,et al.(2021) Research on crop classification based on GF-2 Satellite. J. Geomatics and Spatial Information Technology, 44(04): 158-161.","journal-title":"J. Geomatics and Spatial Information Technology"},{"issue":"23","key":"e_1_3_2_1_4_1","first-page":"188","article-title":"Cultivated land extraction based on GF-1\/WFV remote sensing in Shenwu irrigation area of Hetao Irrigation District","volume":"33","author":"Chang B.H.","year":"2017","unstructured":"Chang , B.H. , Wang , J.T. , Luo , Y.l. , ( 2017 ) Cultivated land extraction based on GF-1\/WFV remote sensing in Shenwu irrigation area of Hetao Irrigation District . J. Transactions of the Chinese Society of Agricultural Engineering , 33 ( 23 ): 188 - 195 . Chang,B.H., Wang,J.T., Luo,Y.l., (2017)Cultivated land extraction based on GF-1\/WFV remote sensing in Shenwu irrigation area of Hetao Irrigation District. J. Transactions of the Chinese Society of Agricultural Engineering, 33(23): 188-195.","journal-title":"J. Transactions of the Chinese Society of Agricultural Engineering"},{"issue":"01","key":"e_1_3_2_1_5_1","first-page":"103","article-title":"Extraction of Crop Planting Structure Based on GF-1 and MODIS Sequential NDVI Characteristics","volume":"37","author":"Li J.B.","year":"2020","unstructured":"Li , J.B. , Wang , H.F. , Zhang , A.B. , ( 2020 ) Extraction of Crop Planting Structure Based on GF-1 and MODIS Sequential NDVI Characteristics . J. Journal of Hebei University of Engineering (Natural Science Edition) , 37 ( 01 ): 103 - 108 . Li,J.B., Wang,H.F., Zhang,A.B., (2020) Extraction of Crop Planting Structure Based on GF-1 and MODIS Sequential NDVI Characteristics. J. Journal of Hebei University of Engineering (Natural Science Edition), 37(01): 103-108.","journal-title":"J. Journal of Hebei University of Engineering (Natural Science Edition)"},{"key":"e_1_3_2_1_6_1","volume-title":"Long Time Series Land Cover Classification in China from 1982 to 2015 Based on Bi-LSTM Deep Learning. J. Remote Sensing, 11(14)","author":"Wang H.","year":"2019","unstructured":"Wang , H. , Zhao , X. , Zhang , X. , ( 2019 ) Long Time Series Land Cover Classification in China from 1982 to 2015 Based on Bi-LSTM Deep Learning. J. Remote Sensing, 11(14) . Wang,H., Zhao,X., Zhang,X., (2019) Long Time Series Land Cover Classification in China from 1982 to 2015 Based on Bi-LSTM Deep Learning. J. Remote Sensing, 11(14)."},{"issue":"01","key":"e_1_3_2_1_7_1","first-page":"115","article-title":"Cotton extraction method of integrated multi-features based on multitemporal Landsat 8 images","volume":"21","author":"Wang W.J.","year":"2017","unstructured":"Wang , W.J. , Zhang , X. , Zhao , Y.D. , ( 2017 ) Cotton extraction method of integrated multi-features based on multitemporal Landsat 8 images . J. Journal of Remote Sensing , 21 ( 01 ): 115 - 124 . Wang,W.J., Zhang,X., Zhao,Y.D., (2017) Cotton extraction method of integrated multi-features based on multitemporal Landsat 8 images. J. Journal of Remote Sensing, 21(01): 115-124.","journal-title":"J. Journal of Remote Sensing"},{"issue":"05","key":"e_1_3_2_1_8_1","first-page":"938","article-title":"Crop Planting Area Extraction based on Google Earth Engine and NDVI Time Series Difference Index","volume":"23","author":"Jiang Y.L.","year":"2021","unstructured":"Jiang , Y.L. , Chen , B.W. , Huang , Y.F. , ( 2021 ) Crop Planting Area Extraction based on Google Earth Engine and NDVI Time Series Difference Index . J. Journal of Geo-Information Science , 23 ( 05 ): 938 - 947 . Jiang,Y.L., Chen,B.W., Huang,Y.F., (2021) Crop Planting Area Extraction based on Google Earth Engine and NDVI Time Series Difference Index. J. Journal of Geo-Information Science,23(05): 938-947.","journal-title":"J. Journal of Geo-Information Science"},{"issue":"01","key":"e_1_3_2_1_9_1","first-page":"83","article-title":"Crop classification based on Sentinel 2A \/B time series data in Heilonggang river basin","volume":"37","author":"Song H.L.","year":"2021","unstructured":"Song , H.L. , Lei , H.M. , Shang , M. ( 2021 ) Crop classification based on Sentinel 2A \/B time series data in Heilonggang river basin . J. Journal of Jiangsu Agricultural Sciences , 37 ( 01 ): 83 - 92 . Song,H.L., Lei,H.M., Shang,M.(2021) Crop classification based on Sentinel 2A \/B time series data in Heilonggang river basin. J. Journal of Jiangsu Agricultural Sciences, 37(01): 83-92.","journal-title":"J. Journal of Jiangsu Agricultural Sciences"},{"issue":"01","key":"e_1_3_2_1_10_1","first-page":"7","article-title":"Analysis on the status,superiority and self-sufficiency ratio of maize in China","volume":"40","author":"Chen Y.J.","year":"2019","unstructured":"Chen , Y.J. , Wang , Q.Q. , Xiang , Y. ( 2019 ) Analysis on the status,superiority and self-sufficiency ratio of maize in China . J. China Agricultural Resources and Regional Planning , 40 ( 01 ): 7 - 16 . Chen,Y.J., Wang,Q.Q., Xiang,Y. (2019)Analysis on the status,superiority and self-sufficiency ratio of maize in China. J. China Agricultural Resources and Regional Planning, 40(01): 7-16.","journal-title":"J. China Agricultural Resources and Regional Planning"},{"issue":"01","key":"e_1_3_2_1_11_1","first-page":"116","article-title":"Impact of Natural Disasters on Maize Yield and Analysis of Meteorological Factors in Western Inner Mongolia","volume":"37","author":"Qiu P.C.","year":"2021","unstructured":"Qiu , P.C. , Du , Y.C. , Chang , G.G. ( 2021 ) Impact of Natural Disasters on Maize Yield and Analysis of Meteorological Factors in Western Inner Mongolia . J. Chinese Agricultural Science Bulletin , 37 ( 01 ): 116 - 120 . Qiu,P.C., Du,Y.C., Chang,G.G.(2021) Impact of Natural Disasters on Maize Yield and Analysis of Meteorological Factors in Western Inner Mongolia. J. Chinese Agricultural Science Bulletin, 37(01): 116-120.","journal-title":"J. Chinese Agricultural Science Bulletin"},{"key":"e_1_3_2_1_12_1","unstructured":"Lian L.J.(2021) Features and Suggestions for the Development of Corn Industry in Inner Mongolia. J. Northern Economy (05): 32-34.  Lian L.J.(2021) Features and Suggestions for the Development of Corn Industry in Inner Mongolia. J. Northern Economy (05): 32-34."},{"issue":"03","key":"e_1_3_2_1_13_1","first-page":"270","article-title":"The Breeding and Plant Technology of New Maize Variety Chidan 109 with High Quality and Starch","volume":"35","author":"Zheng W.","year":"2021","unstructured":"Zheng , W. , Meng , F.S. , Bian . L.M. , ( 2021 ) The Breeding and Plant Technology of New Maize Variety Chidan 109 with High Quality and Starch . J. Crop Research , 35 ( 03 ): 270 - 273 . Zheng,W., Meng,F.S., Bian.L.M., (2021) The Breeding and Plant Technology of New Maize Variety Chidan 109 with High Quality and Starch. J. Crop Research, 35(03): 270-273.","journal-title":"J. Crop Research"},{"issue":"4","key":"e_1_3_2_1_14_1","first-page":"114","article-title":"Using MODIS-EVI to Identify Cropping Structure in Plains Along the Yellow River in Inner Mongolia","volume":"40","author":"Jia B.Z.","year":"2021","unstructured":"Jia , B.Z. , Bai , Y.Y. , Wei , Z.M. , ( 2021 ) Using MODIS-EVI to Identify Cropping Structure in Plains Along the Yellow River in Inner Mongolia . J. Journal of Irrigation and Drainage , 40 ( 4 ): 114 - 120 . Jia,B.Z., Bai,Y.Y., Wei,Z.M., (2021) Using MODIS-EVI to Identify Cropping Structure in Plains Along the Yellow River in Inner Mongolia. J. Journal of Irrigation and Drainage, 40(4): 114-120.","journal-title":"J. Journal of Irrigation and Drainage"},{"issue":"11","key":"e_1_3_2_1_15_1","first-page":"134","article-title":"Crop information identification based on MODIS NDVI time-series data.J","volume":"30","author":"Xu Q.Y.","year":"2014","unstructured":"Xu , Q.Y. , Yang , G.J. , Long , H.L. , ( 2014 ) Crop information identification based on MODIS NDVI time-series data.J . Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE) , 30 ( 11 ): 134 - 144 . Xu,Q.Y., Yang,G.J., Long,H.L., (2014) Crop information identification based on MODIS NDVI time-series data.J. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 30(11): 134-144.","journal-title":"Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE)"},{"issue":"04","key":"e_1_3_2_1_16_1","first-page":"893","article-title":"Extraction of crop planting structure based on time-series NDVI of Landsat8 images","volume":"42","author":"Bai Y.Y.","year":"2019","unstructured":"Bai , Y.Y. , Gao , J.L. , Zhang , B.L. ( 2019 ) Extraction of crop planting structure based on time-series NDVI of Landsat8 images . J. Arid Zone Geography , 42 ( 04 ): 893 - 901 . Bai,Y.Y., Gao,J.L., Zhang,B.L.(2019) Extraction of crop planting structure based on time-series NDVI of Landsat8 images. J. Arid Zone Geography, 42(04): 893-901.","journal-title":"J. Arid Zone Geography"},{"issue":"04","key":"e_1_3_2_1_17_1","first-page":"156","article-title":"Paddy Rice Planting Area Extraction in County-level Based on Spatiotemporal Data Fusion","volume":"51","author":"Niu H.P.","year":"2020","unstructured":"Niu , H.P. , Wang , Z.Q. , Xiao , D.Y. ( 2020 ) Paddy Rice Planting Area Extraction in County-level Based on Spatiotemporal Data Fusion . J. Transactions of the Chinese Society of Agricultural Machinery , 51 ( 04 ): 156 - 163 . Niu,H.P., Wang,Z.Q., Xiao,D.Y.(2020) Paddy Rice Planting Area Extraction in County-level Based on Spatiotemporal Data Fusion. J. Transactions of the Chinese Society of Agricultural Machinery, 51(04): 156-163.","journal-title":"J. Transactions of the Chinese Society of Agricultural Machinery"},{"issue":"15","key":"e_1_3_2_1_18_1","first-page":"129","article-title":"Crop classification based on multi-source remote sensing data fusion and LSTM algorithm","volume":"35","author":"Xie Y.","year":"2019","unstructured":"Xie , Y. , Zhang , Y.Q. , Xun , L. , Chai , X.R. ( 2019 ) Crop classification based on multi-source remote sensing data fusion and LSTM algorithm . J. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE) , 35 ( 15 ): 129 - 137 . Xie,Y., Zhang,Y.Q., Xun,L., Chai,X.R.(2019) Crop classification based on multi-source remote sensing data fusion and LSTM algorithm. J. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 35(15): 129-137.","journal-title":"J. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE)"},{"key":"#cr-split#-e_1_3_2_1_19_1.1","doi-asserted-by":"crossref","unstructured":"Li J.T. Shen Y.L. Yang C.(2020).An Adversarial Generative Network for Crop Classification from Remote Sensing Timeseries Images.\u00a0J.Remote Sensing(1) doi:10.3390\/RS13010065. 10.3390\/RS13010065","DOI":"10.3390\/rs13010065"},{"key":"#cr-split#-e_1_3_2_1_19_1.2","doi-asserted-by":"crossref","unstructured":"Li J.T. Shen Y.L. Yang C.(2020).An Adversarial Generative Network for Crop Classification from Remote Sensing Timeseries Images.\u00a0J.Remote Sensing(1) doi:10.3390\/RS13010065.","DOI":"10.3390\/rs13010065"},{"key":"e_1_3_2_1_20_1","unstructured":"LUO C. LIU H.J. LU L.P. etal(2021).Monthly composites from Sentinel-1 and Sentinel-2 images for regional major crop mapping with Google Earth Engine. J.Journal of Integrative Agriculture(07) 1944-1957. doi:CNKI:SUN:ZGNX.0.2021-07-020.  LUO C. LIU H.J. LU L.P. et al.(2021).Monthly composites from Sentinel-1 and Sentinel-2 images for regional major crop mapping with Google Earth Engine. J.Journal of Integrative Agriculture(07) 1944-1957. doi:CNKI:SUN:ZGNX.0.2021-07-020."},{"key":"#cr-split#-e_1_3_2_1_21_1.1","doi-asserted-by":"crossref","unstructured":"Wang D. Liu C.A. Zeng Y. etal(2021).Dryland Crop Classification Combining Multitype Features and Multitemporal Quad-Polarimetric RADARSAT-2 Imagery in Hebei Plain China.J.Sensors(2) doi:10.3390\/S21020332. 10.3390\/S21020332","DOI":"10.3390\/s21020332"},{"key":"#cr-split#-e_1_3_2_1_21_1.2","doi-asserted-by":"crossref","unstructured":"Wang D. Liu C.A. Zeng Y. et al.(2021).Dryland Crop Classification Combining Multitype Features and Multitemporal Quad-Polarimetric RADARSAT-2 Imagery in Hebei Plain China.J.Sensors(2) doi:10.3390\/S21020332.","DOI":"10.3390\/s21020332"},{"key":"#cr-split#-e_1_3_2_1_22_1.1","doi-asserted-by":"crossref","unstructured":"Kang Y.P. Meng Q.Y. Liu M. etal(2021).Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data.J. Sensors (Basel Switzerland)(13) doi:10.3390\/S21134328 10.3390\/S21134328","DOI":"10.3390\/s21134328"},{"key":"#cr-split#-e_1_3_2_1_22_1.2","doi-asserted-by":"crossref","unstructured":"Kang Y.P. Meng Q.Y. Liu M. et al.(2021).Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data.J. Sensors (Basel Switzerland)(13) doi:10.3390\/S21134328","DOI":"10.3390\/s21134328"}],"event":{"name":"ICCIR 2022: 2022 2nd International Conference on Control and Intelligent Robot","acronym":"ICCIR 2022","location":"Nanjing China"},"container-title":["Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3548608.3559275","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3548608.3559275","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:10:22Z","timestamp":1750183822000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3548608.3559275"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,24]]},"references-count":25,"alternative-id":["10.1145\/3548608.3559275","10.1145\/3548608"],"URL":"https:\/\/doi.org\/10.1145\/3548608.3559275","relation":{},"subject":[],"published":{"date-parts":[[2022,6,24]]},"assertion":[{"value":"2022-10-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}