-
1
-
-
84887105216
-
Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps
-
Mulla DJ. Twenty five years of remote sensing in precision agriculture: key advances and remaining knowledge gaps. Biosyst Eng. 2013;114(4):358-71.
-
(2013)
Biosyst Eng
, vol.114
, Issue.4
, pp. 358-371
-
-
Mulla, D.J.1
-
2
-
-
85015673933
-
Mapping drought-impacted vegetation stress in california using remote sensing
-
Rao M, Silber-Coats Z, Powers S, Fox L III, Ghulam A. Mapping drought-impacted vegetation stress in california using remote sensing. GIsci Remote Sens. 2017;54(2):185-201.
-
(2017)
GIsci Remote Sens
, vol.54
, Issue.2
, pp. 185-201
-
-
Rao, M.1
Silber-Coats, Z.2
Powers, S.3
Fox, L.4
Ghulam, A.5
-
3
-
-
84868629775
-
The application of small unmanned aerial systems for precision agriculture: a review
-
Zhang C, Kovacs JM. The application of small unmanned aerial systems for precision agriculture: a review. Precis Agric. 2012;13(6):693-712.
-
(2012)
Precis Agric
, vol.13
, Issue.6
, pp. 693-712
-
-
Zhang, C.1
Kovacs, J.M.2
-
4
-
-
85019942927
-
Unmanned aerial vehicles for high-throughput phenotyping and agronomic research
-
Shi Y, Thomasson JA, Murray SC, Pugh NA, Rooney WL, Shafian S, Rajan N, Rouze G, Morgan CLS, Neely HL, Rana A, Bagavathiannan MV, Henrickson J, Bowden E, Valasek J, Olsenholler J, Bishop MP, Sheridan R, Putman EB, Popescu S, Burks T, Cope D, Ibrahim A, McCutchen BF, Baltensperger DD, Avant RV Jr, Vidrine M, Yang C. Unmanned aerial vehicles for high-throughput phenotyping and agronomic research. PloS ONE. 2016;11(7):0159781.
-
(2016)
PloS ONE
, vol.11
, Issue.7
, pp. 159781
-
-
Shi, Y.1
Thomasson, J.A.2
Murray, S.C.3
Pugh, N.A.4
Rooney, W.L.5
Shafian, S.6
Rajan, N.7
Rouze, G.8
Morgan, C.L.S.9
Neely, H.L.10
Rana, A.11
Bagavathiannan, M.V.12
Henrickson, J.13
Bowden, E.14
Valasek, J.15
Olsenholler, J.16
Bishop, M.P.17
Sheridan, R.18
Putman, E.B.19
Popescu, S.20
Burks, T.21
Cope, D.22
Ibrahim, A.23
McCutchen, B.F.24
Baltensperger, D.D.25
Avant, R.V.26
Vidrine, M.27
Yang, C.28
more..
-
5
-
-
84922998703
-
UAVs challenge to assess water stress for sustainable agriculture
-
Gago J, Douthe C, Coopman RE, Gallego PP, Ribas-Carbo M, Flexas J, Escalona J, Medrano H. UAVs challenge to assess water stress for sustainable agriculture. Agric Water Manag. 2015;153:9-19.
-
(2015)
Agric Water Manag
, vol.153
, pp. 9-19
-
-
Gago, J.1
Douthe, C.2
Coopman, R.E.3
Gallego, P.P.4
Ribas-Carbo, M.5
Flexas, J.6
Escalona, J.7
Medrano, H.8
-
6
-
-
84975755388
-
Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries
-
Haghighattalab A, Pérez LG, Mondal S, Singh D, Schinstock D, Rutkoski J, Ortiz-Monasterio I, Singh RP, Goodin D, Poland J. Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries. Plant Methods. 2016;12(1):35.
-
(2016)
Plant Methods
, vol.12
, Issue.1
, pp. 35
-
-
Haghighattalab, A.1
Pérez, L.G.2
Mondal, S.3
Singh, D.4
Schinstock, D.5
Rutkoski, J.6
Ortiz-Monasterio, I.7
Singh, R.P.8
Goodin, D.9
Poland, J.10
-
7
-
-
84932599006
-
Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
-
Zaman-Allah M, Vergara O, Araus JL, Tarekegne A, Magorokosho C, Zarco-Tejada PJ, Hornero A, Albà AH, Das B, Craufurd P, Prasanna BM, Cairns J. Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize. Plant Methods. 2015;11(35):1.
-
(2015)
Plant Methods
, vol.11
, Issue.35
, pp. 1
-
-
Zaman-Allah, M.1
Vergara, O.2
Araus, J.L.3
Tarekegne, A.4
Magorokosho, C.5
Zarco-Tejada, P.J.6
Hornero, A.7
Albà, A.H.8
Das, B.9
Craufurd, P.10
Prasanna, B.M.11
Cairns, J.12
-
8
-
-
0029520087
-
A review of vegetation indices
-
Bannari A, Morin D, Bonn F, Huete AR. A review of vegetation indices. Remote Sens Rev. 1995;13(1-2):95-120.
-
(1995)
Remote Sens Rev
, vol.13
, Issue.1-2
, pp. 95-120
-
-
Bannari, A.1
Morin, D.2
Bonn, F.3
Huete, A.R.4
-
9
-
-
84939166594
-
Sensitivity analysis of vegetation indices to drought over two tallgrass prairie sites
-
Bajgain R, Xiao X, Wagle P, Basara J, Zhou Y. Sensitivity analysis of vegetation indices to drought over two tallgrass prairie sites. ISPRS J Photogramm Remote Sens. 2015;108:151-60.
-
(2015)
ISPRS J Photogramm Remote Sens
, vol.108
, pp. 151-160
-
-
Bajgain, R.1
Xiao, X.2
Wagle, P.3
Basara, J.4
Zhou, Y.5
-
10
-
-
85043765967
-
Use of vegetation indices to detect plant diseases
-
In: GIL Jahrestagung
-
Gröll K, Graeff S, Claupein W. Use of vegetation indices to detect plant diseases. In: GIL Jahrestagung. 2007. p. 95-8. https://subs.emis.de/LNI/Proceedings/Proceedings101/article1354.html.
-
(2007)
, pp. 95-98
-
-
Gröll, K.1
Graeff, S.2
Claupein, W.3
-
11
-
-
84964379240
-
Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements
-
Chavana-Bryant C, Malhi Y, Wu J, Asner GP, Anastasiou A, Enquist BJ, Caravasi C, Eric G, Doughty CE, Saleska SR, Martin RE, Gerard FF. Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements. New Phytol. 2016;214(3):1049-63.
-
(2016)
New Phytol
, vol.214
, Issue.3
, pp. 1049-1063
-
-
Chavana-Bryant, C.1
Malhi, Y.2
Wu, J.3
Asner, G.P.4
Anastasiou, A.5
Enquist, B.J.6
Caravasi, C.7
Eric, G.8
Doughty, C.E.9
Saleska, S.R.10
Martin, R.E.11
Gerard, F.F.12
-
12
-
-
85035787290
-
Comparative performance of ground versus aerially assessed rgb and multispectral indices for early-growth evaluation of maize performance under phosphorus fertilization
-
Gracia-Romero A, Kefauver SC, Vergara-Diaz O, Zaman-Allah MA, Prasanna BM, Cairns JE, Araus JL. Comparative performance of ground versus aerially assessed rgb and multispectral indices for early-growth evaluation of maize performance under phosphorus fertilization. Front Plant Sci. 2017;8:2004.
-
(2017)
Front Plant Sci
, vol.8
, pp. 2004
-
-
Gracia-Romero, A.1
Kefauver, S.C.2
Vergara-Diaz, O.3
Zaman-Allah, M.A.4
Prasanna, B.M.5
Cairns, J.E.6
Araus, J.L.7
-
13
-
-
79958119857
-
Use of normalised difference vegetation index, nitrogen concentration, and total nitrogen content of whole maize plant and plant fractions to estimate yield and nutritive value of hybrid forage maize
-
Islam MR, Garcia SCY, Henry D. Use of normalised difference vegetation index, nitrogen concentration, and total nitrogen content of whole maize plant and plant fractions to estimate yield and nutritive value of hybrid forage maize. Crop Pasture Sci. 2011;62(5):374-82.
-
(2011)
Crop Pasture Sci
, vol.62
, Issue.5
, pp. 374-382
-
-
Islam, M.R.1
Garcia, S.C.Y.2
Henry, D.3
-
14
-
-
80051774000
-
Application of vegetation indices for agricultural crop yield prediction using neural network techniques
-
Panda SS, Ames DP, Panigrahi S. Application of vegetation indices for agricultural crop yield prediction using neural network techniques. Remote Sens. 2010;2(3):673-96.
-
(2010)
Remote Sens
, vol.2
, Issue.3
, pp. 673-696
-
-
Panda, S.S.1
Ames, D.P.2
Panigrahi, S.3
-
15
-
-
0002872223
-
Monitoring vegetation systems in the great plains with ERTS
-
Rouse Jr J, Haas RH, Schell JA, Deering DW. Monitoring vegetation systems in the great plains with ERTS. In: Third earth resources technology satellite-1 symposium, vol. 1; 1974. p. 309-17
-
(1974)
In: Third earth resources technology satellite-1 symposium
, vol.1
, pp. 309-317
-
-
Rouse, J.1
Haas, R.H.2
Schell, J.A.3
Deering, D.W.4
-
16
-
-
0030453414
-
Use of a green channel in remote sensing of global vegetation from EOS-MODIS
-
Gitelson AA, Kaufman YJ, Merzlyak MN. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sens Environ. 1996;58(3):289-98.
-
(1996)
Remote Sens Environ
, vol.58
, Issue.3
, pp. 289-298
-
-
Gitelson, A.A.1
Kaufman, Y.J.2
Merzlyak, M.N.3
-
17
-
-
84872176008
-
A red-edge spectral index for remote sensing estimation of green lai over agroecosystems
-
Delegido J, Verrelst J, Meza CM, Rivera JP, Alonso L, Moreno J. A red-edge spectral index for remote sensing estimation of green lai over agroecosystems. Eur J Agron. 2013;46:42-52.
-
(2013)
Eur J Agron
, vol.46
, pp. 42-52
-
-
Delegido, J.1
Verrelst, J.2
Meza, C.M.3
Rivera, J.P.4
Alonso, L.5
Moreno, J.6
-
18
-
-
0024165401
-
A soil-adjusted vegetation index (SAVI)
-
Huete AR. A soil-adjusted vegetation index (SAVI). Remote Sens Environ. 1988;25(3):295-309.
-
(1988)
Remote Sens Environ
, vol.25
, Issue.3
, pp. 295-309
-
-
Huete, A.R.1
-
19
-
-
0036846393
-
Overview of the radiometric and biophysical performance of the modis vegetation indices
-
Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG. Overview of the radiometric and biophysical performance of the modis vegetation indices. Remote Sens Environ. 2002;83(1-2):195-213.
-
(2002)
Remote Sens Environ
, vol.83
, Issue.1-2
, pp. 195-213
-
-
Huete, A.1
Didan, K.2
Miura, T.3
Rodriguez, E.P.4
Gao, X.5
Ferreira, L.G.6
-
20
-
-
85035765532
-
High-throughput phenotyping of plant height: comparing unmanned aerial vehicles and ground LiDAR estimates
-
Madec S, Baret F, De Solan B, Thomas S, Dutartre D, Jezequel S, Hemmerlé M, Colombeau G, Comar A. High-throughput phenotyping of plant height: comparing unmanned aerial vehicles and ground LiDAR estimates. Front Plant Sci. 2017;8:2002.
-
(2017)
Front Plant Sci
, vol.8
, pp. 2002
-
-
Madec, S.1
Baret, F.2
De Solan, B.3
Thomas, S.4
Dutartre, D.5
Jezequel, S.6
Hemmerlé, M.7
Colombeau, G.8
Comar, A.9
-
21
-
-
81055126659
-
Getting NDVI spectral bands from a single standard RGB digital camera: a methodological approach
-
In: Conference of the Spanish association for artificial intelligence. Berlin: Springer
-
Rabatel G, Gorretta N, Labbé S. Getting NDVI spectral bands from a single standard RGB digital camera: a methodological approach. In: Conference of the Spanish association for artificial intelligence. Berlin: Springer; 2011. p. 333-342
-
(2011)
, pp. 333-342
-
-
Rabatel, G.1
Gorretta, N.2
Labbé, S.3
-
22
-
-
84875176667
-
Strategy for the development of a smart NDVI camera system for outdoor plant detection and agricultural embedded systems
-
Dworak V, Selbeck J, Dammer K-H, Hoffmann M, Zarezadeh AA, Bobda C. Strategy for the development of a smart NDVI camera system for outdoor plant detection and agricultural embedded systems. Sensors. 2013;13(2):1523-38.
-
(2013)
Sensors
, vol.13
, Issue.2
, pp. 1523-1538
-
-
Dworak, V.1
Selbeck, J.2
Dammer, K.-H.3
Hoffmann, M.4
Zarezadeh, A.A.5
Bobda, C.6
-
23
-
-
84873971128
-
Small format optical sensors for measuring vegetation indices in remote sensing applications: a comparative approach
-
Muda MA, Foulonneau A, Bigue L, Sudibyo H, Sudiana D. Small format optical sensors for measuring vegetation indices in remote sensing applications: a comparative approach. In: TENCON region 10 conference. IEEE; 2012. p. 1-6.
-
(2012)
In: TENCON region 10 conference. IEEE
, pp. 1-6
-
-
Muda, M.A.1
Foulonneau, A.2
Bigue, L.3
Sudibyo, H.4
Sudiana, D.5
-
24
-
-
84910651844
-
Deep learning in neural networks: an overview
-
Schmidhuber J. Deep learning in neural networks: an overview. Neural Netw. 2015;61:85-117.
-
(2015)
Neural Netw
, vol.61
, pp. 85-117
-
-
Schmidhuber, J.1
-
25
-
-
85040715789
-
The use of plant models in deep learning: An application to leaf counting in rosette plants
-
Ubbens J, Cieslak M, Prusinkiewicz P, Stavness I. The use of plant models in deep learning: an application to leaf counting in rosette plants. Plant Methods. 2018;14(1):6.
-
(2018)
Plant Methods
, vol.14
, Issue.1
, pp. 6
-
-
Ubbens, J.1
Cieslak, M.2
Prusinkiewicz, P.3
Stavness, I.4
-
26
-
-
85033404576
-
TasselNet: counting maize tassels in the wild via local counts regression network
-
Lu H, Cao Z, Xiao Y, Zhuang B, Shen C. TasselNet: counting maize tassels in the wild via local counts regression network. Plant Methods. 2017;13(1):79.
-
(2017)
Plant Methods
, vol.13
, Issue.1
, pp. 79
-
-
Lu, H.1
Cao, Z.2
Xiao, Y.3
Zhuang, B.4
Shen, C.5
-
27
-
-
85053578756
-
Cotton bloom detection using aerial images and convolutional neural network
-
Xu R, Li C, Paterson A, Jiang Y, Sun S, Robertson J. Cotton bloom detection using aerial images and convolutional neural network. Front Plant Sci. 2017;8:2235.
-
(2017)
Front Plant Sci
, vol.8
, pp. 2235
-
-
Xu, R.1
Li, C.2
Paterson, A.3
Jiang, Y.4
Sun, S.5
Robertson, J.6
-
28
-
-
85026457441
-
Deep plant phenomics: a deep learning platform for complex plant phenotyping tasks
-
Ubbens JR, Stavness I. Deep plant phenomics: a deep learning platform for complex plant phenotyping tasks. Front Plant Sci. 2017;8:1190.
-
(2017)
Front Plant Sci
, vol.8
, pp. 1190
-
-
Ubbens, J.R.1
Stavness, I.2
-
29
-
-
85032854973
-
Deep machine learning provides state-of-the-art performance in image-based plant phenotyping
-
Pound MP, Burgess AJ, Wilson MH, Atkinson JA, Griffiths M, Jackson AS, Bulat A, Tzimiropoulos G, Wells DM, Murchie EH, Pridmore TP, French AP. Deep machine learning provides state-of-the-art performance in image-based plant phenotyping. GigaScience. 2017;6(10):1-10.
-
(2017)
GigaScience
, vol.6
, Issue.10
, pp. 1-10
-
-
Pound, M.P.1
Burgess, A.J.2
Wilson, M.H.3
Atkinson, J.A.4
Griffiths, M.5
Jackson, A.S.6
Bulat, A.7
Tzimiropoulos, G.8
Wells, D.M.9
Murchie, E.H.10
Pridmore, T.P.11
French, A.P.12
-
30
-
-
85035097883
-
Panicle-SEG: a robust image segmentation method for rice panicles in the field based on deep learning and superpixel optimization
-
Xiong X, Duan L, Liu L, Tu H, Yang P, Wu D, Chen G, Xiong L, Yang W, Liu Q. Panicle-SEG: a robust image segmentation method for rice panicles in the field based on deep learning and superpixel optimization. Plant Methods. 2017;13(1):104.
-
(2017)
Plant Methods
, vol.13
, Issue.1
, pp. 104
-
-
Xiong, X.1
Duan, L.2
Liu, L.3
Tu, H.4
Yang, P.5
Wu, D.6
Chen, G.7
Xiong, L.8
Yang, W.9
Liu, Q.10
-
31
-
-
85038942809
-
Fine-grained recognition of plants from images
-
Šulc M, Matas J. Fine-grained recognition of plants from images. Plant Methods. 2017;13(1):115.
-
(2017)
Plant Methods
, vol.13
, Issue.1
, pp. 115
-
-
Šulc, M.1
Matas, J.2
-
32
-
-
84988564472
-
Using deep learning for image-based plant disease detection
-
Mohanty SP, Hughes DP, Salathé M. Using deep learning for image-based plant disease detection. Front Plant Sci. 2016;7:1419.
-
(2016)
Front Plant Sci
, vol.7
, pp. 1419
-
-
Mohanty, S.P.1
Hughes, D.P.2
Salathé, M.3
-
36
-
-
84937522268
-
Going deeper with convolutions
-
Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, Erhan D, Vanhoucke V, Rabinovich A. Going deeper with convolutions. In: Conference on computer vision and pattern recognition (CVPR). IEEE; 2015. p. 1-9.
-
(2015)
In: Conference on computer vision and pattern recognition (CVPR). IEEE
, pp. 1-9
-
-
Szegedy, C.1
Liu, W.2
Jia, Y.3
Sermanet, P.4
Reed, S.5
Anguelov, D.6
Erhan, D.7
Vanhoucke, V.8
Rabinovich, A.9
-
37
-
-
84913555165
-
Caffe: convolutional architecture for fast feature embedding
-
Jia Y, Shelhamer E, Donahue J, Karayev S, Long J, Girshick R, Guadarrama S, Darrell T. Caffe: convolutional architecture for fast feature embedding. 2014. arXiv:abs/1408.5093.
-
(2014)
-
-
Jia, Y.1
Shelhamer, E.2
Donahue, J.3
Karayev, S.4
Long, J.5
Girshick, R.6
Guadarrama, S.7
Darrell, T.8
-
38
-
-
79959829092
-
Recurrent neural network based language model
-
Mikolov T, Karafiát M, Burget L, Cernockỳ J, Khudanpur S. Recurrent neural network based language model. Interspeech. 2010;2:1045-8.
-
(2010)
Interspeech
, vol.2
, pp. 1045-1048
-
-
Mikolov, T.1
Karafiát, M.2
Burget, L.3
Cernockỳ, J.4
Khudanpur, S.5
|