Plant Phenotyping Datasets for Computer Vision,
2016
WWW Link.
Dataset, Plants. We present a collection of benchmark datasets in the context of plant
phenotyping. We provide annotated imaging data and suggest suitable
evaluation criteria for plant/leaf segmentation, detection, tracking
as well as classification and regression problems. The figure
symbolically depicts the data available together with ground truth
segmentations and further annotations and metadata.
Article in press.
See also Finely-grained annotated datasets for image-based plant phenotyping.
Subramanian, R.[Ram],
Spalding, E.P.[Edgar P.],
Ferrier, N.J.[Nicola J.],
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MVA(24), No. 3, April 2013, pp. 619-636.
WWW Link.
1303
BibRef
Minervini, M.,
Scharr, H.,
Tsaftaris, S.,
Image Analysis: The New Bottleneck in Plant Phenotyping,
SPMag(32), No. 4, July 2015, pp. 126-131.
IEEE DOI
1506
[Applications Corner]
Agriculture
BibRef
Minervini, M.[Massimo],
Fischbachb, A.[Andreas],
Scharrb, H.[Hanno],
Tsaftarisa, S.A.[Sotirios A.],
Finely-grained annotated datasets for image-based plant phenotyping,
PRL(81), No. 1, 2016, pp. 80-89.
Elsevier DOI
PDF File.
The dataset:
See also Plant Phenotyping Datasets for Computer Vision.
BibRef
1600
Scharr, H.[Hanno],
Dee, H.[Hannah],
French, A.P.[Andrew P.],
Tsaftaris, S.A.[Sotirios A.],
Special issue on computer vision and image analysis in plant
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MVA(27), No. 5, July 2016, pp. 607-609.
Springer DOI
1608
BibRef
Golbach, F.[Franck],
Kootstra, G.[Gert],
Damjanovic, S.[Sanja],
Otten, G.[Gerwoud],
van de Zedde, R.[Rick],
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Springer DOI
1608
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Kelly, D.[Derek],
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Springer DOI
1608
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Cruz, J.A.[Jeffrey A.],
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Springer DOI
1608
BibRef
Pound, M.P.[Michael P.],
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Springer DOI
1608
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Patrick, A.[Aaron],
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High Throughput Phenotyping of Blueberry Bush Morphological Traits
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Elsevier DOI
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Elsevier DOI
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Cao, M.Y.[Meng-Ying],
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Ma, D.D.[Dong-Dong],
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Wang, H.Z.[Hao-Zhou],
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de Lutio, R.[Riccardo],
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Elsevier DOI
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Species recognition, Community science,
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BibRef
Huang, X.[Xia],
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RS(14), No. 2, 2022, pp. xx-yy.
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Rincón, M.G.[Manuel García],
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Taylor, S.D.[Shawn D.],
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Li, D.W.[Da-Wei],
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Elsevier DOI
2202
Plant phenotyping, Point cloud, Semantic segmentation,
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BibRef
Li, C.[Cheng],
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He, J.F.[Jian-Feng],
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Response of Vegetation Phenology to the Interaction of Temperature
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2203
BibRef
Basak, R.[Rinku],
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A Rapid, Low-Cost, and High-Precision Multifrequency Electrical
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2208
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Long, Z.[Zexu],
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Roberts, N.J.[Nathan James],
Su, H.J.[Hai-Jun],
Jiang, G.S.[Guang-Shun],
Wavelet Analysis Reveals Phenology Mismatch between Leaf Phenology of
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RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Li, M.Y.[Meng-Yu],
Yang, W.[Wei],
Kondoh, A.[Akihiko],
Improving Remote Estimation of Vegetation Phenology Using GCOM-C/SGLI
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RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Du, R.M.[Rui-Ming],
Ma, Z.H.[Zhi-Hong],
Xie, P.[Pengyao],
He, Y.[Yong],
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PST: Plant segmentation transformer for 3D point clouds of rapeseed
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PandRS(195), 2023, pp. 380-392.
Elsevier DOI
2301
3D deep learning, Point cloud segmentation,
Handheld laser scanning, Plant phenotyping
BibRef
Esser, F.[Felix],
Klingbeil, L.[Lasse],
Zabawa, L.[Lina],
Kuhlmann, H.[Heiner],
Quality Analysis of a High-Precision Kinematic Laser Scanning System
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RS(15), No. 4, 2023, pp. xx-yy.
DOI Link
2303
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Gobin, A.[Anne],
Sallah, A.H.M.[Abdoul-Hamid Mohamed],
Curnel, Y.[Yannick],
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Advances in the Application of Small Unoccupied Aircraft Systems
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Recent Data Augmentation Strategies for Deep Learning in Plant
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DICTA20(1-8)
IEEE DOI
2201
Training, Deep learning, Pipelines, Training data, Data models,
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ICPR21(10173-10179)
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Deep learning, Image segmentation, Shape, Annotations, Estimation,
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BAT Optimized CNN Model Identifies Water Stress in Chickpea Plant
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ICPR21(8500-8506)
IEEE DOI
2105
Training, Proteins, Computational modeling, Plants (biology), Tools,
Agriculture, Real-time systems, BAT optimization,
plant phenotyping
BibRef
Hutton, J.J.,
Lipa, G.,
Baustian, D.,
Sulik, J.,
Bruce, R.W.,
High Accuracy Direct Georeferencing of the Altum Multi-spectral UAV
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Fine-Grained Recognition in High-throughput Phenotyping,
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IEEE DOI
2008
Feature extraction, Histograms, Image recognition, Task analysis,
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Automatic Generation of Geometric Parameters of Individual Cauliflower
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1912
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Estimating Plant Centers Using A Deep Binary Classifier,
Southwest18(105-108)
IEEE DOI
1809
Unmanned aerial vehicles, Agriculture, Image segmentation, Shape,
Chemicals, Image analysis, Genetics, Plant Phenotyping,
CNN
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Goswami, S.,
Bashyam, S.,
Awada, T.,
Samal, A.,
Automated Stem Angle Determination for Temporal Plant Phenotyping
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Cameras, Colored noise, Image color analysis, Image segmentation,
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CVPPP17(2038-2045)
IEEE DOI
1802
Cameras, Image color analysis, Indoor environments, Lighting, Soil,
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Atkinson, J.A.,
Wells, D.M.,
Pridmore, T.P.,
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Deep Learning for Multi-task Plant Phenotyping,
CVPPP17(2055-2063)
IEEE DOI
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Lall, B.,
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MVA17(428-431)
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1708
Feature extraction, Image segmentation, Microscopy, Morphology,
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Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Precision Agriculture Tools .