-
1
-
-
77952844108
-
Fast High‐Dimensional Filtering Using the Permutohedral Lattice
-
Adams, A., J., Baek, and M. A., Davis. 2010. “Fast High‐Dimensional Filtering Using the Permutohedral Lattice.” Computer Graphics Forum 29 (2): 753–762. doi:10.1111/j.1467-8659.2009.01645.x.
-
(2010)
Computer Graphics Forum
, vol.29
, Issue.2
, pp. 753-762
-
-
Adams, A.1
Baek, J.2
Davis, M.A.3
-
2
-
-
85017602253
-
Detection of Flavescence Dorée Grapevine Disease Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery
-
Albetis, J., S., Duthoit, F., Guttler, A., Jacquin, M., Goulard, H., Poilvé, J.-B., Féret, et al. 2017. “Detection of Flavescence Dorée Grapevine Disease Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery.” Remote Sensing 9 (4): 308. doi:10.3390/rs9040308.
-
(2017)
Remote Sensing
, vol.9
, Issue.4
, pp. 308
-
-
Albetis, J.1
Duthoit, S.2
Guttler, F.3
Jacquin, A.4
Goulard, M.5
Poilvé, H.6
Féret, J.-B.7
-
3
-
-
0027136392
-
Using Satellite Data to Map False Broomweed (Ericameria Austrotexana) Infestations on South Texas Rangelands
-
Anderson, G. L., J. H., Everitt, A. J., Richardson, and D. E., Escobar. 1993. “Using Satellite Data to Map False Broomweed (Ericameria Austrotexana) Infestations on South Texas Rangelands.” Weed Technology 7 (4): 865–871. doi:10.1017/S0890037X00037908.
-
(1993)
Weed Technology
, vol.7
, Issue.4
, pp. 865-871
-
-
Anderson, G.L.1
Everitt, J.H.2
Richardson, A.J.3
Escobar, D.E.4
-
4
-
-
0001812168
-
Multiresolution Segmentation: An Optimization Approach for High Quality Multi-scale Image Segmentation
-
Karlsruhe, Germany: WichmannVerlag
-
Baatz, M., and A., Schäpe. 2000. “Multiresolution Segmentation: An Optimization Approach for High Quality Multi-scale Image Segmentation.” Angewandte Geographische Informationsverarbeitung XII, Karlsruhe, Germany, WichmannVerlag.
-
(2000)
Angewandte Geographische Informationsverarbeitung XII
-
-
Baatz, M.1
Schäpe, A.2
-
5
-
-
84961834117
-
Random Forest in Remote Sensing: A Review of Applications and Future Directions
-
Belgiu, M., and L., Drăguţ. 2016. “Random Forest in Remote Sensing: A Review of Applications and Future Directions.” ISPRS Journal of Photogrammetry and Remote Sensing 114: 24–31. doi:10.1016/j.isprsjprs.2016.01.011.
-
(2016)
ISPRS Journal of Photogrammetry and Remote Sensing
, vol.114
, pp. 24-31
-
-
Belgiu, M.1
Drăguţ, L.2
-
6
-
-
73249139477
-
Object Based Image Analysis for Remote Sensing
-
Blaschke, T., 2010. “Object Based Image Analysis for Remote Sensing.” ISPRS Journal of Photogrammetry and Remote Sensing 65 (1): 2–16. doi:10.1016/j.isprsjprs.2009.06.004.
-
(2010)
ISPRS Journal of Photogrammetry and Remote Sensing
, vol.65
, Issue.1
, pp. 2-16
-
-
Blaschke, T.1
-
7
-
-
77955993281
-
Learning Mid-level Features for Recognition
-
Boureau, Y. L., F., Bach, Y., Lecun, and J., Ponce. 2010. “Learning Mid-level Features for Recognition.” Computer Vision & Pattern Recognition, San Francisco, CA, USA.
-
(2010)
Computer Vision & Pattern Recognition, San Francisco, CA, USA.
-
-
Boureau, Y.L.1
Bach, F.2
Lecun, Y.3
Ponce, J.4
-
9
-
-
0032594951
-
Support Vector Machines for Histogram-based Image Classification
-
Chapelle, O., P., Haffner, and V. N., Vapnik. 1999. “Support Vector Machines for Histogram-based Image Classification.” IEEE Transactions on Neural Networks 10 (5): 1055–1064. doi:10.1109/72.788646.
-
(1999)
IEEE Transactions on Neural Networks
, vol.10
, Issue.5
, pp. 1055-1064
-
-
Chapelle, O.1
Haffner, P.2
Vapnik, V.N.3
-
10
-
-
85042712042
-
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
-
Chen, L. C., G., Papandreou, I., Kokkinos, K., Murphy, and A. L., Yuille. 2018. “DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (4): 834–848. doi:10.1109/TPAMI.2017.2699184.
-
(2018)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.40
, Issue.4
, pp. 834-848
-
-
Chen, L.C.1
Papandreou, G.2
Kokkinos, I.3
Murphy, K.4
Yuille, A.L.5
-
11
-
-
84904466762
-
A Python-based Open Source System for Geographic Object-based Image Analysis (Geobia) Utilizing Raster Attribute Tables
-
Clewley, D., P., Bunting, J., Shepherd, S., Gillingham, N., Flood, J., Dymond, R., Lucas, et al. 2014. “A Python-based Open Source System for Geographic Object-based Image Analysis (Geobia) Utilizing Raster Attribute Tables.” Remote Sensing 6 (7): 6111–6135. doi:10.3390/rs6076111.
-
(2014)
Remote Sensing
, vol.6
, Issue.7
, pp. 6111-6135
-
-
Clewley, D.1
Bunting, P.2
Shepherd, J.3
Gillingham, S.4
Flood, N.5
Dymond, J.6
Lucas, R.7
-
12
-
-
84898446030
-
What Is a Good Evaluation Measure for Semantic Segmentation
-
Bristol, UK
-
Csurka, G., D., Larlus, and F., Perronnin. 2013. “What Is a Good Evaluation Measure for Semantic Segmentation.” BMVC, Bristol, UK.
-
(2013)
BMVC
-
-
Csurka, G.1
Larlus, D.2
Perronnin, F.3
-
13
-
-
85042537525
-
An Automatic Random Forest-obia Algorithm for Early Weed Mapping between and within Crop Rows Using UAV Imagery
-
de Castro, A., J., Torres-Sánchez, J., Peña, F., Jiménez-Brenes, O., Csillik, and F., López-Granados. 2018. “An Automatic Random Forest-obia Algorithm for Early Weed Mapping between and within Crop Rows Using UAV Imagery.” Remote Sensing 10 (3): 285. doi:10.3390/rs10020285.
-
(2018)
Remote Sensing
, vol.10
, Issue.3
, pp. 285
-
-
de Castro, A.1
Torres-Sánchez, J.2
Peña, J.3
Jiménez-Brenes, F.4
Csillik, O.5
López-Granados, F.6
-
14
-
-
80051551703
-
An Optimizing Bp Neural Network Algorithm Based on Genetic Algorithm
-
Ding, S., C., Su, and J., Yu. 2011. “An Optimizing Bp Neural Network Algorithm Based on Genetic Algorithm.” Artificial Intelligence Review 36 (2): 153–162. doi:10.1007/s10462-011-9208-z.
-
(2011)
Artificial Intelligence Review
, vol.36
, Issue.2
, pp. 153-162
-
-
Ding, S.1
Su, C.2
Yu, J.3
-
15
-
-
84904482223
-
Decaf: A Deep Convolutional Activation Feature for Generic Visual Recognition
-
Atlanta, USA
-
Donahue, J., Y., Jia, O., Vinyals, J., Hoffman, N., Zhang, E., Tzeng, and T., Darrell. 2013. “Decaf: A Deep Convolutional Activation Feature for Generic Visual Recognition.” International Conference on Machine Learning, Atlanta, USA.
-
(2013)
International Conference on Machine Learning
-
-
Donahue, J.1
Jia, Y.2
Vinyals, O.3
Hoffman, J.4
Zhang, N.5
Tzeng, E.6
Darrell, T.7
-
16
-
-
53849142529
-
Object-oriented Change Detection for the City of Harare, Zimbabwe
-
Gamanya, R., P., De Maeyer, and M., De Dapper. 2009. “Object-oriented Change Detection for the City of Harare, Zimbabwe.” Expert Systems with Applications 36 (1): 571–588. doi:10.1016/j.eswa.2007.09.067.
-
(2009)
Expert Systems with Applications
, vol.36
, Issue.1
, pp. 571-588
-
-
Gamanya, R.1
De Maeyer, P.2
De Dapper, M.3
-
17
-
-
84993851351
-
Description and Validation of a New Set of Object-based Temporal Geostatistical Features for Land-use/land-cover Change Detection
-
Gil-Yepes, J. L., L. A., Ruiz, J. A., Recio, Á., Balaguer-Beser, and T., Hermosilla. 2016. “Description and Validation of a New Set of Object-based Temporal Geostatistical Features for Land-use/land-cover Change Detection.” ISPRS Journal of Photogrammetry and Remote Sensing 121: 77–91. doi:10.1016/j.isprsjprs.2016.08.010.
-
(2016)
ISPRS Journal of Photogrammetry and Remote Sensing
, vol.121
, pp. 77-91
-
-
Gil-Yepes, J.L.1
Ruiz, L.A.2
Recio, J.A.3
Balaguer-Beser, Á.4
Hermosilla, T.5
-
18
-
-
84986274465
-
Deep Residual Learning for Image Recognition
-
IEEE Computer Society, and,. Las Vegas, NV, USA
-
He, K., X., Zhang, S., Ren, and J., Sun. 2016. “Deep Residual Learning for Image Recognition.” IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, Las Vegas, NV, USA.
-
(2016)
IEEE Conference on Computer Vision and Pattern Recognition
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
19
-
-
84950141946
-
Transferring Deep Convolutional Neural Networks for the Scene Classification of High-resolution Remote Sensing Imagery
-
Hu, F., G. S., Xia, J., Hu, and L., Zhang. 2015. “Transferring Deep Convolutional Neural Networks for the Scene Classification of High-resolution Remote Sensing Imagery.” Remote Sensing 7 (11): 14680–14707. doi:10.3390/rs71114680.
-
(2015)
Remote Sensing
, vol.7
, Issue.11
, pp. 14680-14707
-
-
Hu, F.1
Xia, G.S.2
Hu, J.3
Zhang, L.4
-
20
-
-
85046034633
-
A Fully Convolutional Network for Weed Mapping of Unmanned Aerial Vehicle (UAV) Imagery
-
Huang, H., J., Deng, Y., Lan, A., Yang, X., Deng, and L., Zhang. 2018a. “A Fully Convolutional Network for Weed Mapping of Unmanned Aerial Vehicle (UAV) Imagery.” PLoS One 13 (4): e196302.
-
(2018)
PLoS One
, vol.13
, Issue.4
-
-
Huang, H.1
Deng, J.2
Lan, Y.3
Yang, A.4
Deng, X.5
Zhang, L.6
-
21
-
-
85055732382
-
A Two-stage Classification Approach for the Detection of Spider Mite- Infested Cotton Using UAV Multispectral Imagery
-
Huang, H., J., Deng, Y., Lan, A., Yang, X., Deng, L., Zhang, S., Wen, Y., Jiang, G., Suo, and P., Chen 2018b. “A Two-stage Classification Approach for the Detection of Spider Mite- Infested Cotton Using UAV Multispectral Imagery.” Remote Sensing Letters 9 (10): 933–941. doi:10.1080/2150704X.2018.1498600.
-
(2018)
Remote Sensing Letters
, vol.9
, Issue.10
, pp. 933-941
-
-
Huang, H.1
Deng, J.2
Lan, Y.3
Yang, A.4
Deng, X.5
Zhang, L.6
Wen, S.7
Jiang, Y.8
Suo, G.9
Chen, P.10
-
22
-
-
85049446282
-
A Semantic Labeling Approach for Accurate Weed Mapping of High Resolution UAV Imagery
-
Huang, H., Y., Lan, J., Deng, A., Yang, X., Deng, L., Zhang, and S., Wen. 2018c. “A Semantic Labeling Approach for Accurate Weed Mapping of High Resolution UAV Imagery.” Sensors 18 (7): 2113. doi:10.3390/s18072113.
-
(2018)
Sensors
, vol.18
, Issue.7
, pp. 2113
-
-
Huang, H.1
Lan, Y.2
Deng, J.3
Yang, A.4
Deng, X.5
Zhang, L.6
Wen, S.7
-
23
-
-
33750991392
-
The Effect of the Mycotoxin of α,β-dehydrocurvularin from Curvularia Eragrostidis on Ps Ii in Digitaria Sanguinalis
-
Jiang, S. J., and S., Qiang. 2005. “The Effect of the Mycotoxin of α,β-dehydrocurvularin from Curvularia Eragrostidis on Ps Ii in Digitaria Sanguinalis.” Scientia Agricultura Sinica38(7): 1373-1378.
-
(2005)
Scientia Agricultura Sinica38(7): 1373-1378
-
-
Jiang, S.J.1
Qiang, S.2
-
24
-
-
79957819255
-
Unsupervised Image Segmentation Evaluation and Refinement Using a Multi-scale Approach
-
Johnson, B., and Z., Xie. 2011. “Unsupervised Image Segmentation Evaluation and Refinement Using a Multi-scale Approach.” ISPRS Journal of Photogrammetry and Remote Sensing 66 (4): 473–483. doi:10.1016/j.isprsjprs.2011.02.006.
-
(2011)
ISPRS Journal of Photogrammetry and Remote Sensing
, vol.66
, Issue.4
, pp. 473-483
-
-
Johnson, B.1
Xie, Z.2
-
25
-
-
84897465786
-
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials
-
Krähenbühl, P., and V., Koltun. 2012. “Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials.” arXiv:1210.5644.
-
(2012)
arXiv:1210.5644
-
-
Krähenbühl, P.1
Koltun, V.2
-
27
-
-
84971612769
-
Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks
-
Längkvist, M., A., Kiselev, M., Alirezaie, and A., Loutfi. 2016. “Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks.” Remote Sensing 8 (4): 329. doi:10.3390/rs8040329.
-
(2016)
Remote Sensing
, vol.8
, Issue.4
, pp. 329
-
-
Längkvist, M.1
Kiselev, A.2
Alirezaie, M.3
Loutfi, A.4
-
28
-
-
84930630277
-
Deep Learning
-
Lecun, Y., Y., Bengio, and G., Hinton. 2015. “Deep Learning.” Nature 521 (7553): 436–444. doi:10.1038/nature14539.
-
(2015)
Nature
, vol.521
, Issue.7553
, pp. 436-444
-
-
Lecun, Y.1
Bengio, Y.2
Hinton, G.3
-
29
-
-
71949089395
-
A New Improved BP Neural Network Algorithm
-
Changsha, Hunan, China
-
Li, X., B., Qi, and W., Lu. 2009. “A New Improved BP Neural Network Algorithm.” International Conference on Intelligent Computation Technology & Automation, Changsha, Hunan, China.
-
(2009)
International Conference on Intelligent Computation Technology & Automation
-
-
Li, X.1
Qi, B.2
Lu, W.3
-
30
-
-
85046018583
-
Breeding and Application of High-quality and Diseaseresistant Rice Variety
-
Liu, Y., H., Wang, T., Guo, J., Zhang, X., Tang, and Z., Chen 2013. “Breeding and Application of High-quality and Diseaseresistant Rice Variety.” Guangdong Agricultural Sciences 10: 8–11.
-
(2013)
Guangdong Agricultural Sciences
, vol.10
, pp. 8-11
-
-
Liu, Y.1
Wang, H.2
Guo, T.3
Zhang, J.4
Tang, X.5
Chen, Z.6
-
31
-
-
84939247593
-
Early Season Weed Mapping in Sunflower Using UAV Technology: Variability of Herbicide Treatment Maps against Weed Thresholds
-
López-Granados, F., J., Torres-Sánchez, A., Serrano-Pérez, A. I., de Castro, F.-J., Mesas-Carrascosa, and J.-M., Peña. 2016. “Early Season Weed Mapping in Sunflower Using UAV Technology: Variability of Herbicide Treatment Maps against Weed Thresholds.” Precision Agriculture 17 (2): 183–199. doi:10.1007/s11119-015-9415-8.
-
(2016)
Precision Agriculture
, vol.17
, Issue.2
, pp. 183-199
-
-
López-Granados, F.1
Torres-Sánchez, J.2
Serrano-Pérez, A.3
de Castro, A.I.4
Mesas-Carrascosa, F.-J.5
Peña, J.-M.6
-
32
-
-
85028026239
-
UAV-based Crop and Weed Classification for Smart Farming
-
IEEE, and,. Singapore
-
Lottes, P., R., Khanna, J., Pfeifer, R., Siegwart, and C., Stachniss. 2017. “UAV-based Crop and Weed Classification for Smart Farming.” IEEE International Conference on Robotics & Automation, IEEE, Singapore.
-
(2017)
IEEE International Conference on Robotics & Automation
-
-
Lottes, P.1
Khanna, R.2
Pfeifer, J.3
Siegwart, R.4
Stachniss, C.5
-
33
-
-
0001457509
-
Some Methods for Classification and Analysis of Multivariate Observations
-
University of California, Berkeley, USA
-
Macqueen, J., 1965. “Some Methods for Classification and Analysis of Multivariate Observations.” Proc of Berkeley Symposium on Mathematical Statistics & Probability. University of California, Berkeley, USA.
-
(1965)
Proc of Berkeley Symposium on Mathematical Statistics & Probability
-
-
Macqueen, J.1
-
34
-
-
79960941360
-
Discrimination of Sterile Oat (Avena sterilis) in Winter Barley (Hordeum vulgare) Using Quickbird Satellite Images
-
Martín, M. P., L., Barreto, and C., Fernández-Quintanilla. 2011. “Discrimination of Sterile Oat (Avena sterilis) in Winter Barley (Hordeum vulgare) Using Quickbird Satellite Images.” Crop Protection 30 (10): 1363–1369. doi:10.1016/j.cropro.2011.06.008.
-
(2011)
Crop Protection
, vol.30
, Issue.10
, pp. 1363-1369
-
-
Martín, M.P.1
Barreto, L.2
Fernández-Quintanilla, C.3
-
36
-
-
0029669420
-
A Comparative Study of Texture Measures with Classification Based on Feature Distributions
-
Ojala, T., and I., Harwood. 1996. “A Comparative Study of Texture Measures with Classification Based on Feature Distributions.” Pattern Recognition 29 (1): 51–59. doi:10.1016/0031-3203(95)00067-4.
-
(1996)
Pattern Recognition
, vol.29
, Issue.1
, pp. 51-59
-
-
Ojala, T.1
Harwood, I.2
-
37
-
-
84911449395
-
Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks
-
IEEE, and,. Columbus, Ohio, USA
-
Oquab, M., L., Bottou, I., Laptev, and J., Sivic. 2014. “Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks.” Computer Vision and Pattern Recognition, IEEE, Columbus, Ohio, USA
-
(2014)
Computer Vision and Pattern Recognition
-
-
Oquab, M.1
Bottou, L.2
Laptev, I.3
Sivic, J.4
-
38
-
-
85019750379
-
Evaluation of Hierarchical Self-organising Maps for Weed Mapping Using UAS Multispectral Imagery
-
Pantazi, X. E., A. A., Tamouridou, T. K., Alexandridis, A. L., Lagopodi, J., Kashefi, and D., Moshou. 2017. “Evaluation of Hierarchical Self-organising Maps for Weed Mapping Using UAS Multispectral Imagery.” Computers and Electronics in Agriculture 139: 224–230. doi:10.1016/j.compag.2017.05.026.
-
(2017)
Computers and Electronics in Agriculture
, vol.139
, pp. 224-230
-
-
Pantazi, X.E.1
Tamouridou, A.A.2
Alexandridis, T.K.3
Lagopodi, A.L.4
Kashefi, J.5
Moshou, D.6
-
39
-
-
33947365499
-
Mapping Ridolfia Segetum Patches in Sunflower Crop Using Remote Sensing
-
Peña Barragán, J. M., F., López Granados, M., Jurado Expósito, and L., García‐Torres. 2007. “Mapping Ridolfia Segetum Patches in Sunflower Crop Using Remote Sensing.” Weed Research 47 (2): 164–172. doi:10.1111/j.1365-3180.2007.00553.x.
-
(2007)
Weed Research
, vol.47
, Issue.2
, pp. 164-172
-
-
Peña Barragán, J.M.1
López Granados, F.2
Jurado Expósito, M.3
García‐Torres, L.4
-
40
-
-
84885398102
-
Weed Mapping in Early-season Maize Fields Using Object-based Analysis of Unmanned Aerial Vehicle (UAV) Images
-
Peña JM, Torres-Sánchez J, de Castro AI, Kelly M, and López-Granados F. 2013. “Weed Mapping in Early-season Maize Fields Using Object-based Analysis of Unmanned Aerial Vehicle (UAV) Images.” PloS One 8 (10): e77151. doi:10.1371/journal.pone.0077151.
-
(2013)
PloS One
, vol.8
, Issue.10
-
-
-
41
-
-
85053609099
-
Weedmap: A Large-scale Semantic Weed Mapping Framework Using Aerial Multispectral Imaging and Deep Neural Network for Precision Farming
-
Sa, I., M., Popović, R., Khanna, Z., Chen, P., Lottes, F., Liebisch, and J., Nieto, et al. 2018. “Weedmap: A Large-scale Semantic Weed Mapping Framework Using Aerial Multispectral Imaging and Deep Neural Network for Precision Farming.” Remote Sensing 10 (9): 1423. doi:10.3390/rs10091423.
-
(2018)
Remote Sensing
, vol.10
, Issue.9
, pp. 1423
-
-
Sa, I.1
Popović, M.2
Khanna, R.3
Chen, Z.4
Lottes, P.5
Liebisch, F.6
Nieto, J.7
-
42
-
-
17644437641
-
Advanced Support Vector Machines and Kernel Methods
-
Sánchez, A. V. D., 2003. “Advanced Support Vector Machines and Kernel Methods.” Neurocomputing 55 (1–2): 5–20. doi:10.1016/S0925-2312(03)00373-4.
-
(2003)
Neurocomputing
, vol.55
, Issue.1-2
, pp. 5-20
-
-
Sánchez, A.V.D.1
-
43
-
-
0032016748
-
The Lethal Effects of Cyperus iria on Aedes aegypti
-
Schwartz, A. M., S. M., Paskewitz, A. P., Orth, M. J., Tesch, I. Y., Toong, and W. G., Goodman 1998. “The Lethal Effects of Cyperus iria on Aedes aegypti.” Journal of the American Mosquito Control Association 14 (1): 78.
-
(1998)
Journal of the American Mosquito Control Association
, vol.14
, Issue.1
, pp. 78
-
-
Schwartz, A.M.1
Paskewitz, S.M.2
Orth, A.P.3
Tesch, M.J.4
Toong, I.Y.5
Goodman, W.G.6
-
44
-
-
85077510249
-
-
February, 18
-
Scikit-Learn. 2019 February 18. https://scikit-learn.org/stable/modules/ensemble.html#forest
-
(2019)
-
-
-
45
-
-
85027998504
-
A Patch-based Convolutional Neural Network for Remote Sensing Image Classification
-
Sharma, A., X., Liu, X., Yang, and D., Shi. 2017. “A Patch-based Convolutional Neural Network for Remote Sensing Image Classification.” Neural Networks 95: 19–28. doi:10.1016/j.neunet.2017.07.017.
-
(2017)
Neural Networks
, vol.95
, pp. 19-28
-
-
Sharma, A.1
Liu, X.2
Yang, X.3
Shi, D.4
-
46
-
-
84959205572
-
Fully Convolutional Networks for Semantic Segmentation
-
Boston, Massachusetts, USA
-
Shelhamer, E., J., Long, and T., Darrell. 2015. “Fully Convolutional Networks for Semantic Segmentation.” CVPR, Boston, Massachusetts, USA.
-
(2015)
CVPR
-
-
Shelhamer, E.1
Long, J.2
Darrell, T.3
-
47
-
-
85068119513
-
Operational Large-scale Segmentation of Imagery Based on Iterative Elimination
-
Shepherd, J., P., Bunting, and J., Dymond. 2019. “Operational Large-scale Segmentation of Imagery Based on Iterative Elimination.” Remote Sensing 11 (6): 658. doi:10.3390/rs11060658.
-
(2019)
Remote Sensing
, vol.11
, Issue.6
, pp. 658
-
-
Shepherd, J.1
Bunting, P.2
Dymond, J.3
-
48
-
-
85083953063
-
Very Deep Convolutional Networks for Large-scale Image Recognition
-
San Diego, CA, USA
-
Simonyan, K., and A., Zisserman. 2015. “Very Deep Convolutional Networks for Large-scale Image Recognition.” ICLR, San Diego, CA, USA.
-
(2015)
ICLR
-
-
Simonyan, K.1
Zisserman, A.2
-
50
-
-
84874595926
-
Configuration and Specifications of an Unmanned Aerial Vehicle (UAV) for Early Site Specific Weed Management
-
Torres-Sánchez, J., F., López-Granados, A. I., De Castro, and J. M., Peña-Barragán. 2013. “Configuration and Specifications of an Unmanned Aerial Vehicle (UAV) for Early Site Specific Weed Management.” PloS One 8 (3): e58210. doi:10.1371/journal.pone.0058210.
-
(2013)
PloS One
, vol.8
, Issue.3
-
-
Torres-Sánchez, J.1
López-Granados, F.2
De Castro, A.I.3
Peña-Barragán, J.M.4
-
51
-
-
0032594959
-
An Overview of Statistical Learning Theory
-
Vapnik, V. N., 1999. “An Overview of Statistical Learning Theory.” IEEE Transactions on Neural Networks 10 (5): 988–999. doi:10.1109/72.788640.
-
(1999)
IEEE Transactions on Neural Networks
, vol.10
, Issue.5
, pp. 988-999
-
-
Vapnik, V.N.1
-
52
-
-
85006821297
-
Mechanism of Resistance to Cyhalofop-butyl in Chinese Sprangletop (Leptochloa chinensis (L.) Nees)
-
Yu, J., H., Gao, L., Pan, Z., Yao, and L., Dong. 2017. “Mechanism of Resistance to Cyhalofop-butyl in Chinese Sprangletop (Leptochloa chinensis (L.) Nees).” Pesticide Biochemistry and Physiology 143: 306–311. doi:10.1016/j.pestbp.2016.11.001.
-
(2017)
Pesticide Biochemistry and Physiology
, vol.143
, pp. 306-311
-
-
Yu, J.1
Gao, H.2
Pan, L.3
Yao, Z.4
Dong, L.5
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