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Winter wheat, Water-logging, Parcel scale,
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Xing, S.[Shihe],
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VNIR Data: Effects of View Angles and Plant Architecture,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link
1811
BibRef
Kuester, T.[Theres],
Spengler, D.[Daniel],
Structural and Spectral Analysis of Cereal Canopy Reflectance and
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RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Kanning, M.[Martin],
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Trautz, D.[Dieter],
Jarmer, T.[Thomas],
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RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Zhang, Y.[Yao],
Qin, Q.M.[Qi-Ming],
Ren, H.Z.[Hua-Zhong],
Sun, Y.H.[Yuan-Heng],
Li, M.Z.[Min-Zan],
Zhang, T.Y.[Tian-Yuan],
Ren, S.L.[Shi-Long],
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DOI Link
1901
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El Hajj, M.[Mohammad],
Baghdadi, N.[Nicolas],
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Maize, and Grasslands,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Liu, L.Y.[Lin-Yi],
Dong, Y.Y.[Ying-Ying],
Huang, W.J.[Wen-Jiang],
Du, X.P.[Xiao-Ping],
Luo, J.[Juhua],
Shi, Y.[Yue],
Ma, H.Q.[Hui-Qin],
Enhanced Regional Monitoring of Wheat Powdery Mildew Based on an
Instance-Based Transfer Learning Method,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
BibRef
He, L.,
Coburn, C.A.,
Wang, Z.,
Feng, W.,
Guo, T.,
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GeoRS(57), No. 3, March 2019, pp. 1637-1652.
IEEE DOI
1903
crops, soil, vegetation mapping, reduced prediction saturation,
view effects, leaf area index, winter wheat, vegetation indices, LAI,
winter wheat
BibRef
Yue, J.[Jibo],
Yang, G.[Guijun],
Tian, Q.J.[Qing-Jiu],
Feng, H.[Haikuan],
Xu, K.[Kaijian],
Zhou, C.Q.[Cheng-Quan],
Estimate of winter-wheat above-ground biomass based on UAV
ultrahigh-ground-resolution image textures and vegetation indices,
PandRS(150), 2019, pp. 226-244.
Elsevier DOI
1903
Unmanned aerial vehicle, Vegetation indices,
Ultrahigh ground-resolution image, Image textures,
Reproductive growth stages
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Mapping Winter Wheat Planting Area and Monitoring Its Phenology Using
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1903
BibRef
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Zhou, X.F.[Xian-Feng],
Ye, H.[Huichun],
Casa, R.[Raffaele],
A Comparison of Hybrid Machine Learning Algorithms for the Retrieval
of Wheat Biophysical Variables from Sentinel-2,
RS(11), No. 5, 2019, pp. xx-yy.
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1903
BibRef
He, Y.H.[Yuan-Huizi],
Wang, C.L.[Chang-Lin],
Chen, F.[Fang],
Jia, H.C.[Hui-Cong],
Liang, D.[Dong],
Yang, A.[Aqiang],
Feature Comparison and Optimization for 30-M Winter Wheat Mapping
Based on Landsat-8 and Sentinel-2 Data Using Random Forest Algorithm,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Zhang, C.M.[Cheng-Ming],
Han, Y.J.[Ying-Juan],
Li, F.[Feng],
Gao, S.[Shuai],
Song, D.[Dejuan],
Zhao, H.[Hui],
Fan, K.[Keqi],
Zhang, Y.[Ya'nan],
A New CNN-Bayesian Model for Extracting Improved Winter Wheat Spatial
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RS(11), No. 6, 2019, pp. xx-yy.
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1903
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Yue, J.[Jibo],
Tian, Q.J.[Qing-Jiu],
Dong, X.Y.[Xin-Yu],
Xu, K.J.[Kai-Jian],
Zhou, C.Q.[Cheng-Quan],
Using Hyperspectral Crop Residue Angle Index to Estimate Maize and
Winter-Wheat Residue Cover: A Laboratory Study,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
BibRef
Ma, H.Q.[Hui-Qin],
Huang, W.J.[Wen-Jiang],
Jing, Y.S.[Yuan-Shu],
Yang, C.H.[Cheng-Hai],
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Dong, Y.Y.[Ying-Ying],
Ye, H.C.[Hui-Chun],
Shi, Y.[Yue],
Zheng, Q.[Qiong],
Liu, L.[Linyi],
Ruan, C.[Chao],
Integrating Growth and Environmental Parameters to Discriminate
Powdery Mildew and Aphid of Winter Wheat Using Bi-Temporal Landsat-8
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RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
BibRef
Fernandez-Gallego, J.A.[Jose A.],
Buchaillot, M.L.[Ma. Luisa],
Gutiérrez, N.A.[Nieves Aparicio],
Nieto-Taladriz, M.T.[María Teresa],
Araus, J.L.[José Luis],
Kefauver, S.C.[Shawn C.],
Automatic Wheat Ear Counting Using Thermal Imagery,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
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1905
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A New Integrated Vegetation Index for the Estimation of Winter Wheat
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RS(11), No. 8, 2019, pp. xx-yy.
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1905
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1905
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RS(11), No. 9, 2019, pp. xx-yy.
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1905
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1906
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Zhao, C.Q.[Chun-Qi],
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Jin, X.L.[Xiu-Liang],
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2004
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IEEE DOI
2005
Soil moisture, Soil measurements, Synthetic aperture radar,
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winter wheat
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2005
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2005
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Wheat Yellow Rust Detection Using UAV-Based Hyperspectral Technology,
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2101
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Zhang, X.[Xin],
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Elsevier DOI
2005
Lodging score, Lodging severity, Sentinel-1, RADARSAT-2, PLS-DA,
Sustainable agriculture
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2006
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Winter Wheat Yield Prediction at County Level and Uncertainty
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2006
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Bobylev, L.[Leonid],
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Caluwaerts, S.[Steven],
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Hamdi, R.[Rafiq],
Remedio, A.R.[Armelle Reca],
Sakalli, A.[Abdulla],
van de Vyver, H.[Hans],
van Schaeybroeck, B.[Bert],
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2007
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Segarra, J.[Joel],
González-Torralba, J.[Jon],
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Estimating Wheat Grain Yield Using Sentinel-2 Imagery and Exploring
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2007
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Song, Y.[Yang],
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2008
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2008
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2008
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Kong, W.P.[Wei-Ping],
Yuan, L.[Lin],
Ye, H.[Huichun],
Huang, W.J.[Wen-Jiang],
Assessment of Leaf Chlorophyll Content Models for Winter Wheat Using
Landsat-8 Multispectral Remote Sensing Data,
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2008
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Upreti, D.[Deepak],
Pignatti, S.[Stefano],
Pascucci, S.[Simone],
Tolomio, M.[Massimo],
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Bayesian Calibration of the Aquacrop-OS Model for Durum Wheat by
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2008
BibRef
Lang, T.T.[Ting-Ting],
Yang, Y.Z.[Yan-Zhao],
Jia, K.[Kun],
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Remotely-Sensed Imagery and Process-Based Model Simulations,
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2009
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2009
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Rodríguez-Rastrero, M.[Manuel],
Recuero, L.[Laura],
Huesca, M.[Margarita],
Schmid, T.[Thomas],
Inclán, R.[Rosa],
Litago, J.[Javier],
Sánchez-Girón, V.[Víctor],
Palacios-Orueta, A.[Alicia],
First Insights on Soil Respiration Prediction across the Growth
Stages of Rainfed Barley Based on Simulated MODIS and Sentinel-2
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2009
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Wang, S.[Shuai],
Chen, J.[Jin],
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Liu, L.C.[Li-Cong],
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Elsevier DOI
2009
Spring frost, Winter wheat, Damage assessment, Remote sensing, North China
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Zhu, K.Y.[Kang-Ying],
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Zhao, F.H.[Feng-Hua],
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Long, B.[Buju],
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Elsevier DOI
2009
Remote sensing model, Canopy resistance, Stomatal behavior,
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2009
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Assessing Remote Sensing Vegetation Index Sensitivities for Tall
Fescue (Schedonorus arundinaceus) Plant Health with Varying Endophyte
and Fertilizer Types: A Case for Improving Poultry Manuresheds,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link
2102
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Zhuo, W.[Wen],
Huang, J.X.[Jian-Xi],
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Ma, H.Y.[Hong-Yuan],
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Su, W.[Wei],
Meng, J.[Jihua],
Li, Y.[Ying],
Chen, H.L.[Huai-Liang],
Yin, D.Q.[Dong-Qin],
Prediction of Winter Wheat Maturity Dates through Assimilating
Remotely Sensed Leaf Area Index into Crop Growth Model,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Sapkota, B.[Bishwa],
Singh, V.[Vijay],
Neely, C.[Clark],
Rajan, N.[Nithya],
Bagavathiannan, M.[Muthukumar],
Detection of Italian Ryegrass in Wheat and Prediction of Competitive
Interactions Using Remote-Sensing and Machine-Learning Techniques,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Weiß, T.[Thomas],
Ramsauer, T.[Thomas],
Löw, A.[Alexander],
Marzahn, P.[Philip],
Evaluation of Different Radiative Transfer Models for Microwave
Backscatter Estimation of Wheat Fields,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Xiao, Y.X.[Ying-Xin],
Dong, Y.Y.[Ying-Ying],
Huang, W.J.[Wen-Jiang],
Liu, L.Y.[Lin-Yi],
Ma, H.Q.[Hui-Qin],
Ye, H.C.[Hui-Chun],
Wang, K.[Kun],
Dynamic Remote Sensing Prediction for Wheat Fusarium Head Blight by
Combining Host and Habitat Conditions,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Chen, P.F.[Peng-Fei],
Estimation of Winter Wheat Grain Protein Content Based on Multisource
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2010
BibRef
Song, Y.[Yang],
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Wang, L.X.[Li-Xin],
Satellite Solar-Induced Chlorophyll Fluorescence Reveals Heat Stress
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RS(12), No. 20, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Huang, X.[Xin],
Zhu, W.Q.[Wen-Quan],
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A Method for Monitoring and Forecasting the Heading and Flowering
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RS(12), No. 21, 2020, pp. xx-yy.
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2011
BibRef
Tian, H.F.[Hai-Feng],
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Huang, J.X.[Jian-Xi],
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Wang, J.[Jian],
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Qin, Y.[Yaochen],
Wang, L.[Li],
Garlic and Winter Wheat Identification Based on Active and Passive
Satellite Imagery and the Google Earth Engine in Northern China,
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2011
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Liu, L.[Linyi],
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Ma, H.Q.[Hui-Qin],
Monitoring Wheat Fusarium Head Blight Using Unmanned Aerial Vehicle
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2011
BibRef
Ma, H.Q.[Hui-Qin],
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Dong, Y.Y.[Ying-Ying],
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Guo, A.[Anting],
Using UAV-Based Hyperspectral Imagery to Detect Winter Wheat Fusarium
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2108
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Monitoring Wheat Leaf Rust and Stripe Rust in Winter Wheat Using
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2011
BibRef
Shawon, A.R.[Ashifur Rahman],
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2011
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Image-Based High-Throughput Phenotyping of Cereals Early Vigor and
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2012
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Automatic Evaluation of Wheat Resistance to Fusarium Head Blight
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2101
BibRef
He, L.,
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IEEE DOI
2101
Diseases, Monitoring, Remote sensing, Indexes, Agriculture,
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Zhu, K.Y.[Kang-Ying],
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Relating Hyperspectral Vegetation Indices with Soil Salinity at
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2101
BibRef
Zheng, Q.[Qiong],
Ye, H.C.[Hui-Chun],
Huang, W.J.[Wen-Jiang],
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2101
BibRef
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Elsevier DOI
2102
Canopy temperature, Plant water stress, Vegetation indices,
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RS(13), No. 4, 2021, pp. xx-yy.
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2103
BibRef
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Improved Estimation of Winter Wheat Aboveground Biomass Using
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RS(13), No. 4, 2021, pp. xx-yy.
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2103
BibRef
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Use of Sentinel-1 Multi-Configuration and Multi-Temporal Series for
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2103
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Vegetation Indices Data Clustering for Dynamic Monitoring and
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2103
BibRef
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RS(13), No. 4, 2021, pp. xx-yy.
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2103
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A Neural Network Method for Classification of Sunlit and Shaded
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RS(13), No. 5, 2021, pp. xx-yy.
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2103
BibRef
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Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned
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RS(13), No. 6, 2021, pp. xx-yy.
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2104
BibRef
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Comparison of Regional Winter Wheat Mapping Results from Different
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RS(13), No. 6, 2021, pp. xx-yy.
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2104
BibRef
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RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
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Brandt, M.[Martin],
Prishchepov, A.V.[Alexander V.],
Li, Z.F.[Zhao-Fu],
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Mapping the Dynamics of Winter Wheat in the North China Plain from
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RS(13), No. 6, 2021, pp. xx-yy.
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2104
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Raya-Sereno, M.D.[María D.],
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González-Perez, L.[Lorena],
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High-Resolution Airborne Hyperspectral Imagery for Assessing Yield,
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RS(13), No. 7, 2021, pp. xx-yy.
DOI Link
2104
BibRef
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Dumont, B.[Benjamin],
Mercatoris, B.[Benoît],
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RS(13), No. 7, 2021, pp. xx-yy.
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2104
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Kassouk, Z.[Zeineb],
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Cereal Crops Soil Parameters Retrieval Using L-Band ALOS-2 and C-Band
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RS(13), No. 7, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Wu, B.[Bin],
Huang, W.J.[Wen-Jiang],
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Luo, P.[Peilei],
Ren, Y.[Yu],
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Using Multi-Angular Hyperspectral Data to Estimate the Vertical
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RS(13), No. 8, 2021, pp. xx-yy.
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2104
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2104
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A spectral index for winter wheat mapping using multi-temporal
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Elsevier DOI
2105
Winter wheat mapping, Multi-temporal Landsat NDVI,
Winter wheat index (WWI), Growth stages
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Li, S.L.[Shi-Lei],
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A New Method for Winter Wheat Mapping Based on Spectral
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2105
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Yang, G.J.[Gui-Jun],
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Wheat Fusarium Head Blight Detection Using UAV-Based Spectral and
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2107
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2107
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2107
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2109
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Zhu, Y.[Yan],
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A Wheat Spike Detection Method in UAV Images Based on Improved YOLOv5,
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2109
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Zhao, L.C.[Li-Cheng],
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2109
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Apan, A.[Armando],
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2109
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Khan, I.H.[Imran Haider],
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Early Detection of Powdery Mildew Disease and Accurate Quantification
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2109
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Liu, W.[Wei],
Sun, C.F.[Chao-Fei],
Zhao, Y.[Yanan],
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Xu, X.M.[Xiang-Ming],
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2109
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Peron-Danaher, R.[Raquel],
Russell, B.[Blake],
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Couture, J.J.[John J.],
Incorporating Multi-Scale, Spectrally Detected Nitrogen
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RS(13), No. 19, 2021, pp. xx-yy.
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2110
BibRef
Zhang, T.X.[Tian-Xiang],
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Yang, Z.F.[Zhi-Fang],
Liu, C.[Cunjia],
Chen, W.H.[Wen-Hua],
Li, J.[Jiangyun],
Ir-UNet: Irregular Segmentation U-Shape Network for Wheat Yellow Rust
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RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Kong, W.P.[Wei-Ping],
Huang, W.J.[Wen-Jiang],
Ma, L.L.[Ling-Ling],
Tang, L.[Lingli],
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Zhou, X.F.[Xian-Feng],
Casa, R.[Raffaele],
Estimating Vertical Distribution of Leaf Water Content within Wheat
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RS(13), No. 20, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Eyre, R.[Riley],
Lindsay, J.[John],
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Within-Field Yield Prediction in Cereal Crops Using LiDAR-Derived
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DOI Link
2110
BibRef
Wu, S.R.[Shang-Rong],
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Yang, P.[Peng],
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Evaluation of Winter Wheat Yield Simulation Based on Assimilating LAI
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IEEE DOI
2111
Agriculture, Remote sensing, Synthetic aperture radar,
Optical sensors, Optical imaging, Data models, Yield estimation,
yield simulation
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2112
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Xie, Y.[Yi],
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Integration of a Crop Growth Model and Deep Learning Methods to
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RS(13), No. 21, 2021, pp. xx-yy.
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2112
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Traore, A.[Adama],
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Predicting Equivalent Water Thickness in Wheat Using UAV Mounted
Multispectral Sensor through Deep Learning Techniques,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Zhao, F.[Fa],
Yang, G.[Guijun],
Yang, H.[Hao],
Zhu, Y.H.[Yao-Hui],
Meng, Y.[Yang],
Han, S.Y.[Shao-Yu],
Bu, X.L.[Xin-Lei],
Short and Medium-Term Prediction of Winter Wheat NDVI Based on the
DTW-LSTM Combination Method and MODIS Time Series Data,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
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Zhang, X.Y.[Xiao-Yuan],
Liu, K.[Kai],
Wang, S.D.[Shu-Dong],
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Li, X.[Xueke],
A Rapid Model (COV_PSDI) for Winter Wheat Mapping in Fallow Rotation
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RS(13), No. 23, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Harfenmeister, K.[Katharina],
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Weltzien, C.[Cornelia],
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Detecting Phenological Development of Winter Wheat and Winter Barley
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RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
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Li, Y.S.[Yin-Shuai],
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Zhao, G.X.[Geng-Xing],
Upscaling Remote Sensing Inversion Model of Wheat Field Cultivated
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RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
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Cao, X.F.[Xiao-Feng],
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A Comparison of UAV RGB and Multispectral Imaging in Phenotyping for
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RS(13), No. 24, 2021, pp. xx-yy.
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2112
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Zhou, G.S.[Gui-Sheng],
Tan, C.[Changwei],
Huo, Z.Y.[Zhong-Yang],
UAV- and Machine Learning-Based Retrieval of Wheat SPAD Values at the
Overwintering Stage for Variety Screening,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Bastos, L.M.[Leonardo M.],
Froes de Borja Reis, A.[Andre],
Sharda, A.[Ajay],
Wright, Y.[Yancy],
Ciampitti, I.A.[Ignacio A.],
Current Status and Future Opportunities for Grain Protein Prediction
Using On- and Off-Combine Sensors: A Synthesis-Analysis of the
Literature,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Zhang, Y.X.[Yu-Xi],
Walker, J.P.[Jeffrey P.],
Pauwels, V.R.N.[Valentijn R. N.],
Sadeh, Y.[Yuval],
Assimilation of Wheat and Soil States into the APSIM-Wheat Crop
Model: A Case Study,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Yang, F.F.[Fei-Fei],
Liu, S.P.[Sheng-Ping],
Wang, Q.Y.[Qi-Yuan],
Liu, T.[Tao],
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Assessing Waterlogging Stress Level of Winter Wheat from
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RS(14), No. 1, 2022, pp. xx-yy.
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2201
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Ma, C.Y.[Chun-Yan],
Li, Y.[Yacong],
Li, J.B.[Jing-Bo],
Zhai, W.[Weiguang],
Mapping Winter Wheat with Optical and SAR Images Based on Google
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RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
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Huang, F.[Fujue],
Xia, X.S.[Xing-Sheng],
Huang, Y.S.[Yong-Sheng],
Lv, S.H.[Sheng-Hui],
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Pan, Y.Z.[Yao-Zhong],
Zhu, X.F.[Xiu-Fang],
Comparison of Winter Wheat Extraction Methods Based on Different Time
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RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Zhang, X.C.[Xiao-Chun],
Yuan, X.[Xu],
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Soil Moisture Estimation for Winter-Wheat Waterlogging Monitoring by
Assimilating Remote Sensing Inversion Data into the Distributed
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RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Jing, X.[Xia],
Zou, Q.[Qin],
Yan, J.[Jumei],
Dong, Y.Y.[Ying-Ying],
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Remote Sensing Monitoring of Winter Wheat Stripe Rust Based on
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RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
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Sipols, A.E.[Ana E.],
Valcarce-Diñeiro, R.[Rubén],
Santos-Martín, M.T.[Maria Teresa],
Sánchez, N.[Nilda],
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Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the
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RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
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Bozhanova, V.[Violeta],
Taneva, K.[Krasimira],
Phenotypic Traits Estimation and Preliminary Yield Assessment in
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RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Liu, S.[Shengwei],
Peng, D.[Dailiang],
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Chen, Z.C.[Zheng-Chao],
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Pan, Y.[Yuhao],
Zheng, S.J.[Shi-Jun],
Hu, J.[Jinkang],
Lou, Z.[Zihang],
Chen, Y.[Yue],
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The Accuracy of Winter Wheat Identification at Different Growth
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RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Ahmed, A.A.M.[A. A. Masrur],
Sharma, E.[Ekta],
Jui, S.J.J.[S. Janifer Jabin],
Deo, R.C.[Ravinesh C.],
Nguyen-Huy, T.[Thong],
Ali, M.[Mumtaz],
Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with
Satellite-Derived Predictors,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
BibRef
Ruan, C.[Chao],
Dong, Y.Y.[Ying-Ying],
Huang, W.J.[Wen-Jiang],
Huang, L.S.[Lin-Sheng],
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Ma, H.Q.[Hui-Qin],
Guo, A.[Anting],
Sun, R.Q.[Rui-Qi],
Integrating Remote Sensing and Meteorological Data to Predict Wheat
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RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
BibRef
Wang, F.[Falv],
Yang, M.[Mao],
Ma, L.[Longfei],
Zhang, T.[Tong],
Qin, W.L.[Wei-Long],
Li, W.[Wei],
Zhang, Y.H.[Ying-Hua],
Sun, Z.[Zhencai],
Wang, Z.M.[Zhi-Min],
Li, F.[Fei],
Yu, K.[Kang],
Estimation of Above-Ground Biomass of Winter Wheat Based on
Consumer-Grade Multi-Spectral UAV,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
BibRef
Mikhailenko, I.M.[Ilya Mikhayilovich],
Estimation of Parameters of Biomass State of Sowing Spring Wheat,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Zhang, X.[Xin],
Han, L.X.[Liang-Xiu],
Sobeih, T.[Tam],
Lappin, L.[Lewis],
Lee, M.A.[Mark A.],
Howard, A.[Andew],
Kisdi, A.[Aron],
The Self-Supervised Spectral-Spatial Vision Transformer Network for
Accurate Prediction of Wheat Nitrogen Status from UAV Imagery,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Bian, C.[Chaofa],
Shi, H.T.[Hong-Tao],
Wu, S.[Suqin],
Zhang, K.[Kefei],
Wei, M.[Meng],
Zhao, Y.[Yindi],
Sun, Y.[Yaqin],
Zhuang, H.[Huifu],
Zhang, X.[Xuewei],
Chen, S.[Shuo],
Prediction of Field-Scale Wheat Yield Using Machine Learning Method
and Multi-Spectral UAV Data,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Zare, H.[Hossein],
Weber, T.K.D.[Tobias K. D.],
Ingwersen, J.[Joachim],
Nowak, W.[Wolfgang],
Gayler, S.[Sebastian],
Streck, T.[Thilo],
Combining Crop Modeling with Remote Sensing Data Using a Particle
Filtering Technique to Produce Real-Time Forecasts of Winter Wheat
Yields under Uncertain Boundary Conditions,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Lin, J.Y.[Jing-Yu],
Shen, Q.[Qiu],
Wu, J.J.[Jian-Jun],
Zhao, W.H.[Wen-Hui],
Liu, L.[Leizhen],
Assessing the Potential of Downscaled Far Red Solar-Induced
Chlorophyll Fluorescence from the Canopy to Leaf Level for Drought
Monitoring in Winter Wheat,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Wu, F.[Fei],
Wang, J.[Junchan],
Zhou, Y.[Yuzhuang],
Song, X.X.[Xiao-Xin],
Ju, C.X.[Cheng-Xin],
Sun, C.M.[Cheng-Ming],
Liu, T.[Tao],
Estimation of Winter Wheat Tiller Number Based on Optimization of
Gradient Vegetation Characteristics,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Fan, L.L.[Ling-Ling],
Yang, J.[Jing],
Sun, X.[Xiao],
Zhao, F.[Fen],
Liang, S.F.[She-Fang],
Duan, D.D.[Ding-Ding],
Chen, H.[Hao],
Xia, L.[Lang],
Sun, J.[Jing],
Yang, P.[Peng],
The effects of Landsat image acquisition date on winter wheat
classification in the North China Plain,
PandRS(187), 2022, pp. 1-13.
Elsevier DOI
2205
Multi-temporal, Acquisition dates, Effects evaluation,
Winter wheat, Landsat
BibRef
Cao, J.J.[Jun-Jun],
Wang, H.J.[Hui-Jing],
Li, J.X.[Jin-Xiao],
Tian, Q.[Qun],
Niyogi, D.[Dev],
Improving the Forecasting of Winter Wheat Yields in Northern China
with Machine Learning-Dynamical Hybrid Subseasonal-to-Seasonal
Ensemble Prediction,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Liu, C.X.[Cheng-Xin],
Wang, K.W.[Ke-Wei],
Lu, H.[Hao],
Cao, Z.G.[Zhi-Guo],
Dynamic Color Transform for Wheat Head Detection,
CVPPA21(1278-1283)
IEEE DOI
2112
Head, Uncertainty, Image color analysis, Lighting,
Transforms, Detectors
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Potato Crop Analysis, Production, Detection, Health, Change .