E. Aptoula and B. Yanikoglu, Morphological features for leaf based plant recognition, 2013 IEEE International Conference on Image Processing, p.7, 2013.
DOI : 10.1109/ICIP.2013.6738307

M. Bálint-pál-tóth, D. P. Tóth, and G. Szúcs, Deep learning and svm classification for plant recognition in content-based large scale image retrieval, 2016.

A. Bendale and T. E. Boult, Towards Open World Recognition, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.
DOI : 10.1109/CVPR.2015.7298799

G. Cerutti, L. Tougne, A. Vacavant, and D. Coquin, A Parametric Active Polygon for Leaf Segmentation and Shape Estimation, International Symposium on Visual Computing, pp.202-213, 2011.
DOI : 10.1016/j.cviu.2009.05.002
URL : https://hal.archives-ouvertes.fr/hal-00622269

M. M. Ghazi, B. Yanikoglu, and E. Aptoula, Open-set plant identification using an ensemble of deep convolutional neural networks, 2016.

H. Goëau, J. Champ, and A. Joly, Floristic participation at lifeclef 2016 plant identification task, Working notes of CLEF 2016 conference, 2016.

H. Goëau, A. Joly, S. Selmi, P. Bonnet, E. Mouysset et al., Visual-based plant species identification from crowdsourced data, Proceedings of the 19th ACM international conference on Multimedia, MM '11, pp.813-814, 2011.
DOI : 10.1145/2072298.2072472

S. T. Hang, A. Tatsuma, and M. Aono, Bluefield (kde tut) at lifeclef 2016 plant identification task, 2016.

A. Hazra, K. Deb, S. Kundu, and P. Hazra, Shape Oriented Feature Selection for Tomato Plant Identification, International Journal of Computer Applications Technology and Research, vol.2, issue.4, p.449, 2013.
DOI : 10.7753/IJCATR0204.1011

K. He, X. Zhang, S. Ren, and J. Sun, Deep residual learning for image recognition. arXiv preprint arXiv:1512, p.3385, 2015.

A. Joly, H. Goëau, P. Bonnet, V. Baki´cbaki´c, J. Barbe et al., Interactive plant identification based on social image data, Ecological Informatics, vol.23, pp.22-34, 2014.
DOI : 10.1016/j.ecoinf.2013.07.006
URL : https://hal.archives-ouvertes.fr/hal-00908872

H. Kebapci, B. Yanikoglu, and G. Unal, Plant Image Retrieval Using Color, Shape and Texture Features, The Computer Journal, vol.54, issue.9, pp.1475-1490, 2011.
DOI : 10.1093/comjnl/bxq037

N. Kumar, P. N. Belhumeur, A. Biswas, D. W. Jacobs, W. J. Kress et al., Leafsnap: A Computer Vision System for Automatic Plant Species Identification, European Conference on Computer Vision, pp.502-516, 2012.
DOI : 10.1007/978-3-642-33709-3_36

S. H. Lee, Y. L. Chang, C. S. Chan, and P. Remagnino, Plant identification system based on a convolutional neural network for the lifeclef 2016 plant classification task, 2016.

C. Mccool, Z. Ge, and P. Corke, Feature learning via mixtures of dcnns for finegrained plant classification, 2016.

D. Pimentel, R. Zuniga, and D. Morrison, Update on the environmental and economic costs associated with alien-invasive species in the United States, Ecological Economics, vol.52, issue.3, pp.273-288, 2005.
DOI : 10.1016/j.ecolecon.2004.10.002

W. J. Scheirer, L. P. Jain, and T. E. Boult, Probability Models for Open Set Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.36, issue.11, p.36, 2014.
DOI : 10.1109/TPAMI.2014.2321392

K. Simonyan, A. Zisserman, M. Sulc, D. Mishkin, and J. Matas, Very deep convolutional networks for large-scale image recognition CoRR abs/1409 Very deep residual networks with maxout for plant identification in the wild, 2014.

C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed et al., Going deeper with convolutions, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1-9, 2015.
DOI : 10.1109/CVPR.2015.7298594

E. Weber and D. Gut, Assessing the risk of potentially invasive plant species in central Europe, Journal for Nature Conservation, vol.12, issue.3, pp.171-179, 2004.
DOI : 10.1016/j.jnc.2004.04.002

E. Weber, S. G. Sun, and B. Li, Invasive alien plants in China: diversity and ecological insights, Biological Invasions, vol.18, issue.8, pp.1411-1429, 2008.
DOI : 10.1007/s10530-008-9216-3