19.7.3.7.9 Plants, Leaf Shapes, Leaf Analysis, Leaf Segmentation

Leafsnap,
2011. Vendor, Image Query.
WWW Link. 1106
An electronic field guide combining work from Columbia and Maryland with the resources of the Smithsonian. Initially trees of New York and Maryland. iPhone and iPad apps. Android app to follow.

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Elsevier DOI 0309
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Schatzki, T.F., Witt, S.C., Wilkins, D.E., Lenker, D.H.,
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PR(13), No. 5, 1981, pp. 341-346.
Elsevier DOI 0309
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Combined thresholding and neural network approach for vein pattern extraction from leaf images,
VISP(153), No. 6, December 2006, pp. 881-892.
DOI Link 0702
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Lee, C.L.[Chia-Ling], Chen, S.Y.[Shu-Yuan],
Classification of leaf images,
IJIST(16), No. 1, 2006, pp. 15-23.
DOI Link 0703
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Nam, Y.Y.[Yun-Young], Hwang, E.J.[Een-Jun], Kim, D.Y.[Dong-Yoon],
A similarity-based leaf image retrieval scheme: Joining shape and venation features,
CVIU(110), No. 2, May 2008, pp. 245-259.
Elsevier DOI 0804
Similarity-based image retrieval; Shape-based retrieval; Leaf image retrieval; Venation; MPP; Mobile computing BibRef

Park, J.K.[Jin-Kyu], Hwang, E.J.[Een-Jun], Nam, Y.Y.[Yun-Young],
Utilizing venation features for efficient leaf image retrieval,
JSS(81), No. 1, January, 2008, pp. 71-82.
Elsevier DOI 0905
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Taylor-Hell, J.F.[Julia F.], Baranoski, G.V.G.[Gladimir V. G.], Rokne, J.G.[Jon G.],
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IJIG(5), No. 3, July 2005, pp. 663-678. 0507
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Casanova, D.[Dalcimar], de Mesquita Sá Junior, J.J.[Jarbas Joaci], Bruno, O.M.[Odemir Martinez],
Plant leaf identification using Gabor wavelets,
IJIST(19), No. 3, September 2009, pp. 236-243.
DOI Link 0909
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Xu, G.L.[Gui-Li], Zhang, F.L.[Feng-Ling], Shah, S.G.[Syed Ghafoor], Ye, Y.Q.[Yong-Qiang], Mao, H.P.[Han-Ping],
Use of leaf color images to identify nitrogen and potassium deficient tomatoes,
PRL(32), No. 11, 1 August 2011, pp. 1584-1590.
Elsevier DOI 1108
Classification; Intellective diagnosis; Feature extraction; Feature selection BibRef

Nandyal, S.S.[Suvarna S.], Anami, B.S.[Basavaraj S.], Govardhan, A., Hiremath, P.S.,
A method for identification and classification of medicinal plant images based on level set segmentation and SVM classification,
IJCVR(3), No. 1-2, 2012, pp. 96-114.
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Nandyal, S.S.[Suvarna S.], Anami, B.S.[Basavaraj S.], Govardhan, A.,
Base and apex angles and margin types-based identification and classification from medicinal plants' leaves images,
IJCVR(3), No. 3, 2013, pp. 197-224.
DOI Link 1309
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Hu, R., Jia, W., Ling, H., Huang, D.,
Multiscale Distance Matrix for Fast Plant Leaf Recognition,
IP(21), No. 11, November 2012, pp. 4667-4672.
IEEE DOI 1210
BibRef

Zhang, S.W.[Shan-Wen], Lei, Y.K.[Ying-Ke], Dong, T.B.[Tian-Bao], Zhang, X.P.[Xiao-Ping],
Label propagation based supervised locality projection analysis for plant leaf classification,
PR(46), No. 7, July 2013, pp. 1891-1897.
Elsevier DOI 1303
Label propagation; Warshall algorithm; Plant leaf classification; Supervised locality projection analysis (SLPA) BibRef

Bian, M.[Meng], Skidmore, A.K.[Andrew K.], Schlerf, M.[Martin], Wang, T.J.[Tie-Jun], Liu, Y.F.[Yan-Fang], Zeng, R.[Rong], Fei, T.[Teng],
Predicting foliar biochemistry of tea (Camellia sinensis) using reflectance spectra measured at powder, leaf and canopy levels,
PandRS(78), No. 1, April 2013, pp. 148-156.
Elsevier DOI 1304
Total tea polyphenols; Free amino acids; Soluble sugars; Tea quality; Field spectroscopy; Partial least squares regression BibRef

Cerutti, G.[Guillaume], Tougne, L.[Laure], Mille, J.[Julien], Vacavant, A.[Antoine], Coquin, D.[Didier],
Understanding leaves in natural images: A model-based approach for tree species identification,
CVIU(117), No. 10, 2013, pp. 1482-1501.
Elsevier DOI 1309
BibRef
Earlier: A1, A2, A4, A5, Only:
A Parametric Active Polygon for Leaf Segmentation and Shape Estimation,
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Springer DOI 1109
Plant recognition BibRef

Soares, J.V.B.[João V. B.], Jacobs, D.W.[David W.],
Efficient segmentation of leaves in semi-controlled conditions,
MVA(24), No. 8, November 2013, pp. 1623-1643.
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Kumar, N.[Neeraj], Belhumeur, P.N.[Peter N.], Biswas, A.[Arijit], Jacobs, D.W.[David W.], Kress, W.J.[W. John], Lopez, I.C.[Ida C.], Soares, J.V.B.[João V. B.],
Leafsnap: A Computer Vision System for Automatic Plant Species Identification,
ECCV12(II: 502-516).
Springer DOI 1210
BibRef

Larese, M.G.[Mónica G.], Namías, R.[Rafael], Craviotto, R.M.[Roque M.], Arango, M.R.[Miriam R.], Gallo, C.[Carina], Granitto, P.M.[Pablo M.],
Automatic classification of legumes using leaf vein image features,
PR(47), No. 1, 2014, pp. 158-168.
Elsevier DOI 1310
Leaf vein features BibRef

Lei, Y.K.[Ying-Ke], Zou, J.W.[Ji-Wei], Dong, T.B.[Tian-Bao], You, Z.H.[Zhu-Hong], Yuan, Y.[Yuan], Hu, Y.H.[Yi-Hua],
Orthogonal locally discriminant spline embedding for plant leaf recognition,
CVIU(119), No. 1, 2014, pp. 116-126.
Elsevier DOI 1412
Plant leaf recognition BibRef

Kazmi, W.[Wajahat], Foix, S.[Sergi], Alenyà, G.[Guillem], Andersen, H.J.[Hans Jørgen],
Indoor and outdoor depth imaging of leaves with time-of-flight and stereo vision sensors: Analysis and comparison,
PandRS(88), No. 1, 2014, pp. 128-146.
Elsevier DOI 1412
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Liang, J.[Jie], Zia, A., Zhou, J.[Jun], Sirault, X.,
3D Plant Modelling via Hyperspectral Imaging,
AccBio13(172-177)
IEEE DOI 1403
geophysical image processing BibRef

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Automatic plant identification from photographs,
MVA(25), No. 6, 2014, pp. 1369-1383.
WWW Link. 1408
BibRef
Earlier: A2, A1, Only:
Morphological features for leaf based plant recognition,
ICIP13(1496-1499)
IEEE DOI 1412
Plant recognition BibRef

Wang, B.[Bin], Gao, Y.S.[Yong-Sheng],
Hierarchical String Cuts: A Translation, Rotation, Scale, and Mirror Invariant Descriptor for Fast Shape Retrieval,
IP(23), No. 9, September 2014, pp. 4101-4111.
IEEE DOI 1410
BibRef
Earlier:
Fast and Effective Retrieval of Plant Leaf Shapes,
ACCV12(II:475-486).
Springer DOI 1304
computational geometry BibRef

Johansen, K.[Kasper], Sohlbach, M.[Malte], Sullivan, B.[Barry], Stringer, S.[Samantha], Peasley, D.[David], Phinn, S.[Stuart],
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DOI Link 1410
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Cerutti, G.[Guillaume], Tougne, L.[Laure], Coquin, D.[Didier], Vacavant, A.[Antoine],
Leaf margins as sequences: A structural approach to leaf identification,
PRL(49), No. 1, 2014, pp. 177-184.
Elsevier DOI 1410
Leaf recognition BibRef

Kalyoncu, C.[Cem], Toygar, Ö.[Önsen],
Geometric leaf classification,
CVIU(133), No. 1, 2015, pp. 102-109.
Elsevier DOI 1502
Leaf classification BibRef

Grand-Brochier, M., Vacavant, A., Cerutti, G., Kurtz, C., Weber, J., Tougne, L.,
Tree Leaves Extraction in Natural Images: Comparative Study of Preprocessing Tools and Segmentation Methods,
IP(24), No. 5, May 2015, pp. 1549-1560.
IEEE DOI 1504
biology computing BibRef

Chaki, J.[Jyotismita], Parekh, R.[Ranjan], Bhattacharya, S.[Samar],
Plant leaf recognition using texture and shape features with neural classifiers,
PRL(58), No. 1, 2015, pp. 61-68.
Elsevier DOI 1505
Gabor filter BibRef

Zhao, C.[Cong], Chan, S.S.F.[Sharon S.F.], Cham, W.K.[Wai-Kuen], Chu, L.M.,
Plant identification using leaf shapes: A pattern counting approach,
PR(48), No. 10, 2015, pp. 3203-3215.
Elsevier DOI 1507
Plant identification BibRef

Prasad, S.[Shitala], Peddoju, S.K.[Sateesh K.], Ghosh, D.[Debashis],
Multi-resolution mobile vision system for plant leaf disease diagnosis,
SIViP(10), No. 1, February 2016, pp. 379-388.
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Leaf segmentation in plant phenotyping: a collation study,
MVA(27), No. 4, May 2016, pp. 585-606.
Springer DOI 1605
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Chéné, Y.[Yann], Rousseau, D.[David], Belin, É.[Étienne], Garbez, M.[Morgan], Galopin, G.[Gilles], Chapeau-Blondeau, F.[François],
Shape descriptors to characterize the shoot of entire plant from multiple side views of a motorized depth sensor,
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Springer DOI 1605
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Larese, M.G.[Mónica G.], Granitto, P.M.[Pablo M.],
Finding local leaf vein patterns for legume characterization and classification,
MVA(27), No. 5, July 2016, pp. 709-720.
Springer DOI 1608
BibRef
Earlier:
Hybrid Consensus Learning for Legume Species and Cultivars Classification,
PlantType14(201-214).
Springer DOI 1504
BibRef

Tomar, D.[Divya], Agarwal, S.[Sonali],
Leaf Recognition for Plant Classification Using Direct Acyclic Graph Based Multi-Class Least Squares Twin Support Vector Machine,
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DOI Link 1608
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Champ, J.[Julien], Lorieul, T.[Titouan], Bonnet, P.[Pierre], Maghnaoui, N.[Najate], Sereno, C.[Christophe], Dessup, T.[Thierry], Boursiquot, J.M.[Jean-Michel], Audeguin, L.[Laurent], Lacombe, T.[Thierry], Joly, A.[Alexis],
Categorizing plant images at the variety level: Did you say fine-grained?,
PRL(81), No. 1, 2016, pp. 71-79.
Elsevier DOI 1609
Fine grained classification BibRef

Faria, F.A.[Fabio A.], Almeida, J.[Jurandy], Alberton, B.C.[Bruna C.], Morellato, L.P.C.[Leonor Patricia C.], da Silva Torres, R.[Ricardo],
Fusion of time series representations for plant recognition in phenology studies,
PRL(83, Part 2), No. 1, 2016, pp. 205-214.
Elsevier DOI 1609
Plant species identification BibRef

Almeida, J.[Jurandy], dos Santos, J.A.[Jefersson A.], Alberton, B.C.[Bruna C.], Morellato, L.P.C.[Leonor Patricia C.], da Silva Torres, R.[Ricardo],
Phenological visual rhythms: Compact representations for fine-grained plant species identification,
PRL(81), No. 1, 2016, pp. 90-100.
Elsevier DOI 1609
BibRef
Earlier:
Visual rhythm-based time series analysis for phenology studies,
ICIP13(4412-4416)
IEEE DOI 1412
Plant phenology. Remote phenology BibRef

Faria, F.A.[Fabio A.], Almeida, J.[Jurandy], Alberton, B.[Bruna], Morellato, L.P.C.[Leonor Patricia C.], Rocha, A.[Anderson], da Silva Torres, R.[Ricardo],
Time series-based classifier fusion for fine-grained plant species recognition,
PRL(81), No. 1, 2016, pp. 101-109.
Elsevier DOI 1609
Plant species identification BibRef

Rouahi, H.[Hibat'Allah], Mtibaa, R.[Riadh], Zagrouba, E.[Ezzeddine],
Bayesian Approach in Kendall Shape Space for Plant Species Classification,
IbPRIA17(322-331).
Springer DOI 1706
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Lee, S.H.[Sue Han], Chan, C.S.[Chee Seng], Mayo, S.J.[Simon Joseph], Remagnino, P.[Paolo],
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PR(71), No. 1, 2017, pp. 1-13.
Elsevier DOI 1707
Plant, recognition BibRef

Lee, S.H.[Sue Han], Chan, C.S.[Chee Seng], Remagnino, P.[Paolo],
Multi-Organ Plant Classification Based on Convolutional and Recurrent Neural Networks,
IP(27), No. 9, September 2018, pp. 4287-4301.
IEEE DOI 1807
biology computing, data visualisation, feature extraction, image classification, learning (artificial intelligence), deep learning BibRef

Lee, S.H.[Sue Han], Chang, Y.L., Chan, C.S.[Chee Seng], Remagnino, P.[Paolo],
HGO-CNN: Hybrid generic-organ convolutional neural network for multi-organ plant classification,
ICIP17(4462-4466)
IEEE DOI 1803
Correlation, Feature extraction, Machine learning, Measurement, Task analysis, Training, deep learning BibRef

Lee, S.H.[Sue Han], Chan, C.S.[Chee Seng], Wilkin, P.[Paul], Remagnino, P.[Paolo],
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ICIP15(452-456)
IEEE DOI 1512
deep learning;feature visualisation;plant classification BibRef

Reichmuth, A.[Anne], Henning, L.[Lea], Pinnel, N.[Nicole], Bachmann, M.[Martin], Rogge, D.[Derek],
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IEEE DOI 1805
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ICIP14(408-412)
IEEE DOI 1502
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IEEE DOI 1806
biology computing, botany, convolution, feature extraction, feedforward neural nets, image recognition, image resolution, plant leaf recognition BibRef

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geophysical image processing, geophysical techniques, image segmentation, optical scanners, vegetation, terrestrial laser scanner (TLS) BibRef

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Leaf-Level Spectral Fluorescence Measurements: Comparing Methodologies for Broadleaves and Needles,
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IEEE DOI 1909
Shape, Compounds, Transforms, Legged locomotion, Shape measurement, Feature extraction, Image retrieval, Shape description, Log-Min distance BibRef

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Absorption, Biological system modeling, Machine learning, Estimation, Vegetation mapping, Pigments, machine learning regression BibRef

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Pigments, Biological system modeling, Sensitivity, Correlation, Absorption, Structural engineering, Current measurement, ABM, transmittance BibRef

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Plant leaf recognition, Multiscale triangle descriptor, Local binary pattern, Shape descriptor, Texture feature BibRef

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Deep learning, Instance segmentation, Digitized herbarium specimen images (DHS), Plant leaves, Morphological traits BibRef

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Song, G.Q.[Guang-Qin], Wu, S.B.[Sheng-Biao], Lee, C.K.F.[Calvin K.F.], Serbin, S.P.[Shawn P.], Wolfe, B.T.[Brett T.], Ng, M.K.[Michael K.], Ely, K.S.[Kim S.], Bogonovich, M.[Marc], Wang, J.[Jing], Lin, Z.[Ziyu], Saleska, S.[Scott], Nelson, B.W.[Bruce W.], Rogers, A.[Alistair], Wu, J.[Jin],
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PandRS(183), 2022, pp. 19-33.
Elsevier DOI 2201
Residual Networks, Semantic segmentation, Proximate remote sensing, Leaf quantity, Leaf quality, Phenocam BibRef

Rashwan, S.A.[Shaheera A.], Elteir, M.K.[Marwa K.],
Plant leaf disease detection using deep learning on mobile devices,
IJCVR(12), No. 2, 2022, pp. 156-176.
DOI Link 2203
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Caglayan, A.[Ali], Imamoglu, N.[Nevrez], Nakamura, R.[Ryosuke],
MMSNet: Multi-modal scene recognition using multi-scale encoded features,
IVC(122), 2022, pp. 104453.
Elsevier DOI 2205
RGB-D scene recognition, Multi-modal learning, Multi-scale feature fusion BibRef

Caglayan, A.[Ali], Can, A.B.[Ahmet Burak],
Exploiting Multi-layer Features Using a CNN-RNN Approach for RGB-D Object Recognition,
3DSemantics18(III:675-688).
Springer DOI 1905
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Earlier:
An Empirical Analysis of Deep Feature Learning for RGB-D Object Recognition,
ICIAR17(312-320).
Springer DOI 1706
BibRef
And:
3D convolutional object recognition using volumetric representations of depth data,
MVA17(125-128)
DOI Link 1708
Data models, Feature extraction, Iris recognition, Neural networks, Object recognition, Solid modeling. BibRef

Caglayan, A.[Ali], Guclu, O.[Oguzhan], Can, A.B.[Ahmet Burak],
A Plant Recognition Approach Using Shape and Color Features in Leaf Images,
CIAP13(II:161-170).
Springer DOI 1309
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Chen, X.[Xin], Wang, B.[Bin], Gao, Y.S.[Yong-Sheng],
Symmetric Binary Tree Based Co-occurrence Texture Pattern Mining for Fine-grained Plant Leaf Image Retrieval,
PR(129), 2022, pp. 108769.
Elsevier DOI 2206
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And:
Pairwise Rotational-Difference LBP for Fine-Grained Leaf Image Retrieval,
ICIP22(3346-3350)
IEEE DOI 2211
Leaf image pattern, Species recognition, Fine-grained image recognition, Feature fusion, Image retrieval. Image recognition, Gray-scale, Task analysis, Rotation measurement, spatial co-occurrence feature BibRef

Chen, X.[Xin], Wang, B.[Bin], Gao, Y.S.[Yong-Sheng],
Leaf Vocabulary: Fine-Grained Leaf Image Retrieval Using Bag-of-Visual-Words Representation,
ICPR22(2714-2720)
IEEE DOI 2212
Performance evaluation, Vocabulary, Visualization, Histograms, Shape, Shape measurement, Image retrieval, shape features BibRef

Chen, X.[Xin], You, J.W.[Jia-Wei], Tang, H.[Hui], Wang, B.[Bin], Gao, Y.S.[Yong-Sheng],
Fine-Grained Plant Leaf Image Retrieval Using Local Angle Co-occurrence Histograms,
ICIP21(1599-1603)
IEEE DOI 2201
Deep learning, Histograms, Image recognition, Image coding, Shape, Fuses, Leaf image pattern, species recognition, image retrieval BibRef

Budianti, N.[Noviana], Naramoto, M.[Masaaki], Iio, A.[Atsuhiro],
Drone-Sensed and Sap Flux-Derived Leaf Phenology in a Cool Temperate Deciduous Forest: A Tree-Level Comparison of 17 Species,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
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Han, T.[Tao], Sánchez-Azofeifa, G.A.[Gerardo Arturo],
Extraction of Liana Stems Using Geometric Features from Terrestrial Laser Scanning Point Clouds,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
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Chen, Q.H.[Qin-Han], Yao, L.J.[Li-Jian], Xu, L.J.[Li-Jun], Yang, Y.[Yankun], Xu, T.[Taotao], Yang, Y.C.[Yun-Cong], Liu, Y.[Yu],
Horticultural Image Feature Matching Algorithm Based on Improved ORB and LK Optical Flow,
RS(14), No. 18, 2022, pp. xx-yy.
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Lin, X.F.[Xu-Feng], Li, C.T.[Chang-Tsun], Adams, S.[Scott], Kouzani, A.Z.[Abbas Z.], Jiang, R.[Richard], He, L.G.[Li-Gang], Hu, Y.J.[Yong-Jian], Vernon, M.[Michael], Doeven, E.[Egan], Webb, L.[Lawrence], Mcclellan, T.[Todd], Guskich, A.[Adam],
Self-Supervised Leaf Segmentation under Complex Lighting Conditions,
PR(135), 2023, pp. 109021.
Elsevier DOI 2212
Self-supervised learning, Convolutional neural networks, Image-based plant phenotyping, Leaf segmentation, Cannabis BibRef

Ciocîrlan, M.I.C.[Mihnea Ioan Cezar], Curtu, A.L.[Alexandru Lucian], Radu, G.R.[Gheorghe Raul],
Predicting Leaf Phenology in Forest Tree Species Using UAVs and Satellite Images: A Case Study for European Beech (Fagus sylvatica L.),
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
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Li, X.[Xin], Guo, S.[Siyu], Gong, L.[Linrui], Lan, Y.[Yuan],
An automatic plant leaf stoma detection method based on YOLOv5,
IET-IPR(17), No. 1, 2023, pp. 67-76.
DOI Link 2301
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Li, S.[Sijia], Fang, H.L.[Hong-Liang], Zhang, Y.H.[Ying-Hui],
Determination of the Leaf Inclination Angle (LIA) through Field and Remote Sensing Methods: Current Status and Future Prospects,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
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Almodfer, R.[Rolla], Mudhsh, M.[Mohammed], Zhao, J.[Jifei],
Pyramided and optimized blurred shape model for plant leaf classification,
IET-IPR(17), No. 10, 2023, pp. 2838-2854.
DOI Link 2308
feature extraction, feature selection, image classification, image recognition, optimization BibRef

Xue, F.[Fuduo], Elnashef, B.[Bashar], Jin, W.Q.[Wei-Qi], Filin, S.[Sagi],
Polarimetric monocular leaf normal estimation model for plant phenotyping,
PandRS(202), 2023, pp. 142-157.
Elsevier DOI 2308
Polarization imaging, Normal estimation, Reflectance model, Leaf orientation BibRef

Mei, J.[Jie], Sun, K.Q.[Kai-Qiong], Luo, G.[Gang],
Cross-Domain Leaf Counting with Minimizing Feature Distances,
ICIVC22(812-817)
IEEE DOI 2301
Training, Deep learning, Adaptation models, Costs, Annotations, Computational modeling, Estimation, deep learning, leaf counting, domain adaptation BibRef

Beery, S.[Sara], Wu, G.[Guanhang], Edwards, T.[Trevor], Pavetic, F.[Filip], Majewski, B.[Bo], Mukherjee, S.[Shreyasee], Chan, S.[Stanley], Morgan, J.[John], Rathod, V.[Vivek], Huang, J.[Jonathan],
The Auto Arborist Dataset: A Large-Scale Benchmark for Multiview Urban Forest Monitoring Under Domain Shift,
CVPR22(21262-21275)
IEEE DOI 2210
Training, Measurement, Urban areas, Forestry, Vegetation, Benchmark testing, Datasets and evaluation, Vision applications and systems BibRef

Gozzovelli, R.[Riccardo], Franchetti, B.[Benjamin], Bekmurat, M.[Malik], Pirri, F.[Fiora],
Tip-burn stress detection of lettuce canopy grown in Plant Factories,
CVPPA21(1259-1268)
IEEE DOI 2112
Training, Measurement, Image segmentation, Merging, Search problems, Production facilities, Sensors BibRef

Guo, R.[Ruohao], Qu, L.[Liao], Niu, D.T.[Dan-Tong], Li, Z.B.[Zhen-Bo], Yue, J.[Jun],
LeafMask: Towards Greater Accuracy on Leaf Segmentation,
CVPPA21(1249-1258)
IEEE DOI 2112
Data analysis, Current measurement, Refining, Neural networks, Merging BibRef

Ghazal, M., Mahmoud, A., Shalaby, A., Shaker, S., Khelifi, A., El-Baz, A.,
Precise Statistical Approach for Leaf Segmentation,
ICIP20(2985-2989)
IEEE DOI 2011
Image segmentation, Diseases, Lighting, Gray-scale, Forestry, Support vector machines, Probability distribution, LCDG, GGMRF, Mangrove BibRef

El Abidine, M.Z.[Mouad Zine], Merdinoglu-Wiedemann, S.[Sabine], Rasti, P.[Pejman], Dutagaci, H.[Helin], Rousseau, D.[David],
Machine Learning-based Classification of Powdery Mildew Severity on Melon Leaves,
ICISP20(74-81).
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Khan, N.A., Lyon, O.A.S., Eramian, M., McQuillan, I.,
A Novel Technique Combining Image Processing, Plant Development Properties, and the Hungarian Algorithm, to Improve Leaf Detection in Maize,
AgriVision20(330-339)
IEEE DOI 2008
Skeleton, Image segmentation, Topology, Prediction algorithms, Agriculture BibRef

Ajij, M., Roy, D.S.[D. Sinha], Pratihar, S.,
Plant Leaf Recognition using Geometric Features and Pearson Correlations,
IVCNZ19(1-6)
IEEE DOI 2004
biology computing, botany, feature extraction, image classification, object recognition, shape recognition, leaf categorization BibRef

Haindl, M., Žid, P.,
Coniferous Trees Needles-Based Taxonomy Classification,
IVCNZ19(1-6)
IEEE DOI 2004
biology computing, botany, feature extraction, image classification, image texture, Markov processes, Spiral Markov random field model BibRef

Forero, M.G.[Manuel G.], Perdomo, S.A.[Sammy A.], Quimbaya, M.A.[Mauricio A.], Perez, G.F.[Guillermo F.],
Image Processing Method for Epidermal Cells Detection and Measurement in Arabidopsis Thaliana Leaves,
IbPRIA19(II:416-428).
Springer DOI 1910
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Scabini, L.F.S.[Leonardo F. S.], Condori, R.M.[Rayner M.], Munhoz, I.C.L.[Isabella C. L.], Bruno, O.M.[Odemir M.],
Deep Convolutional Neural Networks for Plant Species Characterization Based on Leaf Midrib,
CAIP19(II:389-401).
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Isokane, T.[Takahiro], Okura, F.[Fumio], Ide, A.[Ayaka], Matsushita, Y.[Yasuyuki], Yagi, Y.S.[Yasu-Shi],
Probabilistic Plant Modeling via Multi-view Image-to-Image Translation,
CVPR18(2906-2915)
IEEE DOI 1812
Probabilistic logic, Bayes methods, Solid modeling, Estimation, Computational modeling BibRef

Bhugra, S., Mishra, D., Anupama, A., Chaudhury, S., Lall, B., Chugh, A.,
Automatic Quantification of Stomata for High-Throughput Plant Phenotyping,
ICPR18(3904-3910)
IEEE DOI 1812
Scanning electron microscopy, Apertures, Image segmentation, Feature extraction, Stress, Morphology BibRef

Chaudhury, A., Barron, J.L.,
Occluded Leaf Matching with Full Leaf Databases Using Explicit Occlusion Modelling,
CRV18(8-15)
IEEE DOI 1812
Splines (mathematics), Shape, Databases, Feature extraction, Measurement, Mathematical model, Energy Optimization BibRef

Ni, F., Wang, B.,
Integral Contour Angle: An Invariant Shape Descriptor for Classification and Retrieval of Leaf Images,
ICIP18(1223-1227)
IEEE DOI 1809
Shape, Feature extraction, Image retrieval, Task analysis, Image color analysis, Shape measurement, leaf identification BibRef

Gélard, W., Herbulot, A., Devy, M., Casadebaig, P.,
3D Leaf Tracking for Plant Growth Monitoring,
ICIP18(3663-3667)
IEEE DOI 1809
Labeling, Monitoring, Spirals, Stress, Motion segmentation, Biomedical monitoring, 3D leaf tracking, Sunflower plants BibRef

Chaisuk, P., Phromsuthirak, K., Areekul, V.,
Leaf classification based on a quadratic curved axis,
ICIP17(4472-4476)
IEEE DOI 1803
Classification algorithms, Databases, Feature extraction, Measurement, Reliability, Shape, Strain, Leaf classification, Plant identification BibRef

Chen, Y., Ribera, J., Boomsma, C., Delp, E.J.,
Plant leaf segmentation for estimating phenotypic traits,
ICIP17(3884-3888)
IEEE DOI 1803
Agriculture, Image color analysis, Image segmentation, Imaging, Indexes, Shape, Unmanned aerial vehicles, color image processing, segmentation BibRef

Shah, M.P., Singha, S., Awate, S.P.,
Leaf classification using marginalized shape context and shape-texture dual-path deep convolutional neural network,
ICIP17(860-864)
IEEE DOI 1803
Convolutional neural networks, Image color analysis, Robustness, Shape, Support vector machines, texture BibRef

Alves, D.H.A.[Daniel H. A.], Galonetti, L.F.[Luís F.], de Oliveira, C.[Claiton], Bugatti, P.H.[Pedro H.], Saito, P.T.M.[Priscila T. M.],
Going Deeper on BioImages Classification: A Plant Leaf Dataset Case Study,
CIARP17(36-44).
Springer DOI 1802
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Beardsley, P., Chaurasia, G.,
Editable Parametric Dense Foliage from 3D Capture,
ICCV17(5315-5324)
IEEE DOI 1802
image colour analysis, image reconstruction, image segmentation, solid modelling, 3d capture, Bezier patches, Bezier representation, BibRef

Dobrescu, A., Giuffrida, M.V., Tsaftaris, S.A.,
Leveraging Multiple Datasets for Deep Leaf Counting,
CVPPP17(2072-2079)
IEEE DOI 1802
Image segmentation, Machine learning, Shape, Testing, Training BibRef

Aich, S., Stavness, I.,
Leaf Counting with Deep Convolutional and Deconvolutional Networks,
CVPPP17(2080-2089)
IEEE DOI 1802
Data models, Image segmentation, Manuals, Training BibRef

Gélard, W.[William], Herbulot, A.[Ariane], Devy, M.[Michel], Debaeke, P.[Philippe], McCormick, R.F.[Ryan F.], Truong, S.K.[Sandra K.], Mullet, J.[John],
Leaves Segmentation in 3D Point Cloud,
ACIVS17(664-674).
Springer DOI 1712
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Wang, B., Gao, Y., Sun, C., Blumenstein, M., Salle, J.L.,
Can Walking and Measuring Along Chord Bunches Better Describe Leaf Shapes?,
CVPR17(2047-2056)
IEEE DOI 1711
Feature extraction, Legged locomotion, Mirrors, Shape, Shape measurement, Transforms BibRef

Du, M.J.[Meng-Jie], Zheng, J.,
Measurement of classify typical planting medicinal Fritillaria Pallidiflora Schrenk with WorldView-2 extraction problem imagery,
ICIVC17(808-811)
IEEE DOI 1708
Biomedical monitoring, Biomedical optical imaging, Monitoring, Optical sensors, Principal component analysis, Standards, WorldView-2, classification, fritillaria pallidiflora schrenk, object-oriented, texture feature, traditional, Chinese, medicine BibRef

Brattland, V.[Vegard], Austvoll, I.[Ivar], Ruoff, P.[Peter], Drengstig, T.[Tormod],
Image Processing of Leaf Movements in Mimosa pudica,
SCIA17(I: 77-87).
Springer DOI 1706
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Ameur, R.B., Valet, L., Coquin, D.,
Sub-classification strategies for tree species recognition,
ICPR16(2139-2144)
IEEE DOI 1705
Adaptive systems, Context, Databases, Pattern recognition, Shape, Silicon, Vegetation BibRef

Olivares, L., Victorino, J., Gómez, F.,
Automatic leaf shape category discovery,
ICPR16(1023-1028)
IEEE DOI 1705
Biology, Databases, Harmonic analysis, Kernel, Manuals, Shape, Visualization, Adaptive mean shift, Leaf shape, Visual, category, discovery BibRef

Frolov, K., Fripp, J., Nguyen, C.V., Furbank, R., Bull, G., Kuffner, P., Daily, H., Sirault, X.,
Automated Plant and Leaf Separation: Application in 3D Meshes of Wheat Plants,
DICTA16(1-7)
IEEE DOI 1701
Cameras BibRef

Yu, X., Xiong, S., Gao, Y., Zhao, Y., Yuan, X.,
Multiscale Crossing Representation Using Combined Feature of Contour and Venation for Leaf Image Identification,
DICTA16(1-6)
IEEE DOI 1701
Feature extraction BibRef

Siravenha, A.C., Carvalho, S.R.,
Plant Classification from Leaf Textures,
DICTA16(1-8)
IEEE DOI 1701
Data mining BibRef

Yu, X.H.[Xiao-Han], Xiong, S.W.[Sheng-Wu], Gao, Y.,
Leaf image retrieval using combined feature of vein and contour,
ICVNZ15(1-6)
IEEE DOI 1701
feature extraction BibRef

Romera-Paredes, B.[Bernardino], Torr, P.H.S.[Philip Hilaire Sean],
Recurrent Instance Segmentation,
ECCV16(VI: 312-329).
Springer DOI 1611
Recurrent NN sequentially find objects. BibRef

Putzu, L.[Lorenzo], di Ruberto, C.[Cecilia], Fenu, G.[Gianni],
A Mobile Application for Leaf Detection in Complex Background Using Saliency Maps,
ACIVS16(570-581).
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El Massi, I., Es-Saady, Y., El Yassa, M., Mammass, D., Benazoun, A.,
Automatic Recognition of the Damages and Symptoms on Plant Leaves Using Parallel Combination of Two Classifiers,
CGiV16(131-136)
IEEE DOI 1608
botany BibRef

Kala, J.R.[Jules Raymond], Viriri, S.[Serestina], Moodley, D.[Deshendran],
Leaf Classification Using Convexity Moments of Polygons,
ISVC16(II: 330-339).
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Kala, J.R.[Jules Raymond], Viriri, S.[Serestina], Moodley, D.[Deshendran], Tapamo, J.R.[Jules Raymond],
Leaf Classification Using Convexity Measure of Polygons,
ICISP16(51-60).
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El Massi, I.[Ismail], Es-Saady, Y.[Youssef], El Yassa, M.[Mostafa], Mammass, D.[Driss], Benazoun, A.[Abdeslam],
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Olsen, A., Han, S., Calvert, B., Ridd, P., Kenny, O.,
In Situ Leaf Classification Using Histograms of Oriented Gradients,
DICTA15(1-8)
IEEE DOI 1603
biology computing BibRef

Rousseau, D.[David], van de Zedde, H.J.[Henricus J.],
Counting leaves without 'finger-counting' by supervised multiscale frequency analysis of depth images from top view,
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Giuffrida, M.V.[Mario Valerio], Minervini, M.[Massimo], Tsaftaris, S.[Sotirios],
Learning to Count Leaves in Rosette Plants,
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Simek, K.[Kyle], Barnard, K.[Kobus],
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Buoncompagni, S.[Simone], Maio, D.[Dario], Lepetit, V.[Vincent],
Leaf Segmentation under Loosely Controlled Conditions,
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Pape, J.M.[Jean-Michel], Klukas, C.[Christian],
Utilizing machine learning approaches to improve the prediction of leaf counts and individual leaf segmentation of rosette plant images,
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Minervini, M.[Massimo], Giuffrida, M.V.[Mario Valerio], Tsaftaris, S.[Sotirios],
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Escobar, M.[María], Berdugo, M.[Mary], Rangel-Ch, O.[Orlando], Gómez, F.[Francisco],
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CIARP15(27-34).
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Oncevay-Marcos, A.[Arturo], Juarez-Chambi, R.[Ronald], Khlebnikov-Núñez, S.[Sofía], Beltrán-Castañón, C.[César],
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Redolfi, J.A.[Javier A.], Sánchez, J.A.[Jorge A.], Pucheta, J.A.[Julián A.],
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Saitoh, T.[Takeshi], Iwata, T.[Toshihiro], Wakisaka, K.[Kentaro],
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Feature extraction BibRef

Zhao, Z.Q.[Zhong-Qiu], Xie, B.J.[Bao-Jian], Cheung, Y.M.[Yiu-Ming], Wu, X.D.[Xin-Dong],
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Augustin, M.[Marco], Haxhimusa, Y.[Yll], Busch, W.[Wolfgang], Kropatsch, W.G.[Walter G.],
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Sulc, M.[Milan], Matas, J.G.[Jiri G.],
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Fast Features Invariant to Rotation and Scale of Texture,
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Pape, J.M.[Jean-Michel], Klukas, C.[Christian],
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Le, T.L.[Thi-Lan], Tran, D.T.[Duc-Tuan], Pham, N.H.[Ngoc-Hai],
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IPTA14(1-5)
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biology computing BibRef

Leemans, V., Dumont, B., Destain, M.F.,
Assessment of plant leaf area measurement by using stereo-vision,
IC3D13(1-5)
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area measurement BibRef

Hall, D.[David], McCool, C.[Chris], Dayoub, F.[Feras], Sunderhauf, N.[Niko], Upcroft, B.[Ben],
Evaluation of Features for Leaf Classification in Challenging Conditions,
WACV15(797-804)
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Accuracy BibRef

Liu, H., Coquin, D., Valet, L., Cerutti, G.,
Leaf Species Classification Based on a Botanical Shape Sub-classifier Strategy,
ICPR14(1496-1501)
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Decision trees BibRef

Yadav, A.R., Dewal, M.L., Anand, R.S., Gupta, S.,
Classification of hardwood species using ANN classifier,
NCVPRIPG13(1-5)
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Díaz, G.[Gloria], Romero, E.[Eduardo], Boyero, J.R.[Juan R.], Malpica, N.[Norberto],
Recognition and Quantification of Area Damaged by Oligonychus Perseae in Avocado Leaves,
CIARP09(677-684).
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Winberg, S., Katz, S., Mishra, A.K.,
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automatic optical inspection BibRef

Vu, H.[Hai], Le, T.L.[Thi-Lan], Tran, T.H.[Thanh-Hai], Nguyen, T.T.[Thuy Thi],
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Kurtek, S.[Sebastian], Laga, H.[Hamid], Xie, Q.[Qian],
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Plant identification BibRef

Mouine, S.[Sofiene], Yahiaoui, I.[Itheri], Verroust-Blondet, A.[Anne],
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ICIP13(1466-1470)
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Advanced shape context for plant species identification using leaf image retrieval,
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